{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": [
     "remove-cell"
    ]
   },
   "outputs": [],
   "source": [
    "# Reference: https://jupyterbook.org/interactive/hiding.html\n",
    "# Use {hide, remove}-{input, output, cell} tags to hiding content\n",
    "\n",
    "import sys\n",
    "import os\n",
    "if not any(path.endswith('textbook') for path in sys.path):\n",
    "    sys.path.append(os.path.abspath('../../..'))\n",
    "from textbook_utils import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": [
     "remove-cell"
    ]
   },
   "outputs": [],
   "source": [
    "def remove_bcs_outliers(donkeys):\n",
    "    return donkeys[(donkeys['BCS'] >= 1.5) & (donkeys['BCS'] <= 4)] \n",
    "\n",
    "def remove_weight_outliers(donkeys):\n",
    "    return donkeys[(donkeys['Weight'] >= 40)]\n",
    "\n",
    "donkeys = (pd.read_csv('data/donkeys.csv')\n",
    "           .pipe(remove_bcs_outliers)\n",
    "           .pipe(remove_weight_outliers))\n",
    "\n",
    "np.random.seed(42)\n",
    "indices = np.arange(len(donkeys))\n",
    "np.random.shuffle(indices)\n",
    "n_train = int(np.round((len(donkeys)*0.8)))\n",
    "\n",
    "train_set = donkeys.iloc[indices[:n_train]]\n",
    "test_set = donkeys.iloc[indices[n_train:]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Modeling a Donkey's Weight\n",
    "\n",
    "We want to build a simple model for predicting the weight of a donkey. The model should be easy for a vet to implement in the field with only a hand calculator. The model should also be easy to interpret.\n",
    "\n",
    "We also want the model to depend on the vet's situation---for example, whether they're prescribing an antibiotic or an anesthetic.\n",
    "For brevity, we only consider the case of prescribing an anesthetic.\n",
    "Our first step is to choose a loss function that reflects this situation."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A Loss Function for Prescribing Anesthetics\n",
    "\n",
    "An overdose of an anesthetic can be much worse than an underdose. It's not hard\n",
    "for a vet to see when a donkey has too little anesthetic (it'll complain), and\n",
    "the vet can give the donkey a bit more. On the other hand, too much anesthetic\n",
    "can have serious consequences and can even be fatal. Because of this, we want\n",
    "an asymmetric loss function: it should have a bigger loss for an overestimate\n",
    "of weight compared to an underestimate. This is in contrast to the other loss\n",
    "functions that we have used so far in this book, which have all been symmetric. \n",
    "\n",
    "We've created a loss function `anes_loss(x)` with this in mind: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def anes_loss(x):\n",
    "    w = (x >= 0) + 3 * (x < 0)\n",
    "    return np.square(x) * w"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The relative error is $100(y - \\hat{y})/\\hat{y}$, where $y$ is the true value and $\\hat{y}$ is the prediction. We can demonstrate the asymmetry of the loss function with a plot:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "hovertemplate": "x=%{x}<br>y=%{y}<extra></extra>",
         "legendgroup": "",
         "line": {
          "color": "#1F77B4",
          "dash": "solid"
         },
         "marker": {
          "symbol": "circle"
         },
         "mode": "lines",
         "name": "",
         "orientation": "v",
         "showlegend": false,
         "type": "scatter",
         "x": [
          -40,
          -39.83967935871743,
          -39.67935871743487,
          -39.519038076152306,
          -39.35871743486974,
          -39.19839679358717,
          -39.03807615230461,
          -38.877755511022045,
          -38.71743486973948,
          -38.55711422845691,
          -38.39679358717435,
          -38.236472945891784,
          -38.07615230460922,
          -37.91583166332666,
          -37.75551102204409,
          -37.59519038076152,
          -37.434869739478955,
          -37.274549098196395,
          -37.11422845691383,
          -36.95390781563126,
          -36.7935871743487,
          -36.633266533066134,
          -36.47294589178357,
          -36.312625250501,
          -36.15230460921844,
          -35.99198396793587,
          -35.831663326653306,
          -35.67134268537074,
          -35.51102204408818,
          -35.35070140280561,
          -35.190380761523045,
          -35.03006012024048,
          -34.86973947895792,
          -34.70941883767535,
          -34.549098196392784,
          -34.388777555110224,
          -34.22845691382766,
          -34.06813627254509,
          -33.90781563126252,
          -33.74749498997996,
          -33.587174348697395,
          -33.42685370741483,
          -33.26653306613227,
          -33.1062124248497,
          -32.945891783567134,
          -32.78557114228457,
          -32.62525050100201,
          -32.46492985971944,
          -32.30460921843687,
          -32.144288577154306,
          -31.983967935871746,
          -31.82364729458918,
          -31.663326653306612,
          -31.50300601202405,
          -31.342685370741485,
          -31.182364729458918,
          -31.02204408817635,
          -30.861723446893787,
          -30.701402805611224,
          -30.541082164328657,
          -30.380761523046093,
          -30.22044088176353,
          -30.060120240480963,
          -29.899799599198396,
          -29.739478957915832,
          -29.57915831663327,
          -29.4188376753507,
          -29.258517034068134,
          -29.09819639278557,
          -28.937875751503007,
          -28.77755511022044,
          -28.617234468937877,
          -28.456913827655313,
          -28.296593186372746,
          -28.13627254509018,
          -27.975951903807616,
          -27.815631262525052,
          -27.655310621242485,
          -27.494989979959918,
          -27.334669338677354,
          -27.17434869739479,
          -27.014028056112224,
          -26.85370741482966,
          -26.693386773547097,
          -26.53306613226453,
          -26.372745490981963,
          -26.2124248496994,
          -26.052104208416836,
          -25.89178356713427,
          -25.7314629258517,
          -25.571142284569138,
          -25.410821643286575,
          -25.250501002004007,
          -25.090180360721444,
          -24.92985971943888,
          -24.769539078156313,
          -24.609218436873746,
          -24.448897795591183,
          -24.28857715430862,
          -24.128256513026052,
          -23.96793587174349,
          -23.80761523046092,
          -23.647294589178358,
          -23.48697394789579,
          -23.326653306613228,
          -23.16633266533066,
          -23.006012024048097,
          -22.845691382765533,
          -22.685370741482966,
          -22.525050100200403,
          -22.364729458917836,
          -22.204408817635272,
          -22.044088176352705,
          -21.88376753507014,
          -21.723446893787575,
          -21.56312625250501,
          -21.402805611222444,
          -21.24248496993988,
          -21.082164328657317,
          -20.92184368737475,
          -20.761523046092186,
          -20.60120240480962,
          -20.440881763527056,
          -20.28056112224449,
          -20.120240480961925,
          -19.95991983967936,
          -19.799599198396795,
          -19.639278557114228,
          -19.478957915831664,
          -19.3186372745491,
          -19.158316633266534,
          -18.99799599198397,
          -18.837675350701403,
          -18.67735470941884,
          -18.517034068136272,
          -18.35671342685371,
          -18.196392785571142,
          -18.03607214428858,
          -17.87575150300601,
          -17.715430861723448,
          -17.555110220440884,
          -17.394789579158317,
          -17.234468937875754,
          -17.074148296593187,
          -16.913827655310623,
          -16.753507014028056,
          -16.593186372745492,
          -16.432865731462925,
          -16.272545090180362,
          -16.112224448897795,
          -15.951903807615231,
          -15.791583166332668,
          -15.6312625250501,
          -15.470941883767537,
          -15.31062124248497,
          -15.150300601202407,
          -14.98997995991984,
          -14.829659318637276,
          -14.669338677354709,
          -14.509018036072145,
          -14.348697394789582,
          -14.188376753507015,
          -14.028056112224451,
          -13.867735470941884,
          -13.70741482965932,
          -13.547094188376754,
          -13.38677354709419,
          -13.226452905811623,
          -13.06613226452906,
          -12.905811623246493,
          -12.745490981963929,
          -12.585170340681366,
          -12.424849699398798,
          -12.264529058116235,
          -12.104208416833668,
          -11.943887775551104,
          -11.783567134268537,
          -11.623246492985974,
          -11.462925851703407,
          -11.302605210420843,
          -11.142284569138276,
          -10.981963927855713,
          -10.82164328657315,
          -10.661322645290582,
          -10.501002004008019,
          -10.340681362725451,
          -10.180360721442888,
          -10.02004008016032,
          -9.859719438877757,
          -9.69939879759519,
          -9.539078156312627,
          -9.37875751503006,
          -9.218436873747496,
          -9.058116232464933,
          -8.897795591182366,
          -8.737474949899802,
          -8.577154308617235,
          -8.416833667334672,
          -8.256513026052104,
          -8.096192384769541,
          -7.935871743486977,
          -7.77555110220441,
          -7.615230460921843,
          -7.454909819639283,
          -7.294589178356716,
          -7.134268537074149,
          -6.973947895791582,
          -6.813627254509022,
          -6.653306613226455,
          -6.492985971943888,
          -6.332665330661321,
          -6.172344689378761,
          -6.012024048096194,
          -5.851703406813627,
          -5.691382765531067,
          -5.5310621242485,
          -5.370741482965933,
          -5.210420841683366,
          -5.050100200400806,
          -4.889779559118239,
          -4.729458917835672,
          -4.569138276553105,
          -4.408817635270545,
          -4.2484969939879775,
          -4.0881763527054105,
          -3.9278557114228505,
          -3.7675350701402834,
          -3.6072144288577164,
          -3.4468937875751493,
          -3.2865731462925893,
          -3.1262525050100223,
          -2.965931863727455,
          -2.805611222444888,
          -2.645290581162328,
          -2.484969939879761,
          -2.324649298597194,
          -2.164328657314634,
          -2.004008016032067,
          -1.8436873747495,
          -1.6833667334669329,
          -1.523046092184373,
          -1.3627254509018059,
          -1.2024048096192388,
          -1.0420841683366717,
          -0.8817635270541118,
          -0.7214428857715447,
          -0.5611222444889776,
          -0.40080160320641767,
          -0.2404809619238506,
          -0.08016032064128353,
          0.08016032064128353,
          0.2404809619238435,
          0.40080160320641056,
          0.5611222444889776,
          0.7214428857715447,
          0.8817635270541047,
          1.0420841683366717,
          1.2024048096192388,
          1.3627254509017988,
          1.5230460921843658,
          1.6833667334669329,
          1.8436873747495,
          2.00400801603206,
          2.164328657314627,
          2.324649298597194,
          2.484969939879761,
          2.645290581162321,
          2.805611222444888,
          2.965931863727455,
          3.126252505010015,
          3.2865731462925822,
          3.4468937875751493,
          3.6072144288577164,
          3.7675350701402763,
          3.9278557114228434,
          4.0881763527054105,
          4.2484969939879775,
          4.4088176352705375,
          4.569138276553105,
          4.729458917835672,
          4.889779559118232,
          5.050100200400799,
          5.210420841683366,
          5.370741482965933,
          5.531062124248493,
          5.69138276553106,
          5.851703406813627,
          6.012024048096194,
          6.172344689378754,
          6.332665330661321,
          6.492985971943888,
          6.653306613226448,
          6.813627254509015,
          6.973947895791582,
          7.134268537074149,
          7.294589178356709,
          7.454909819639276,
          7.615230460921843,
          7.77555110220441,
          7.93587174348697,
          8.096192384769537,
          8.256513026052104,
          8.416833667334664,
          8.577154308617231,
          8.737474949899799,
          8.897795591182366,
          9.058116232464926,
          9.218436873747493,
          9.37875751503006,
          9.539078156312627,
          9.699398797595187,
          9.859719438877754,
          10.02004008016032,
          10.18036072144288,
          10.340681362725448,
          10.501002004008015,
          10.661322645290582,
          10.821643286573142,
          10.981963927855709,
          11.142284569138276,
          11.302605210420836,
          11.462925851703403,
          11.62324649298597,
          11.783567134268537,
          11.943887775551097,
          12.104208416833664,
          12.264529058116231,
          12.424849699398798,
          12.585170340681358,
          12.745490981963925,
          12.905811623246493,
          13.066132264529053,
          13.22645290581162,
          13.386773547094187,
          13.547094188376754,
          13.707414829659314,
          13.86773547094188,
          14.028056112224448,
          14.188376753507015,
          14.348697394789575,
          14.509018036072142,
          14.669338677354709,
          14.829659318637269,
          14.989979959919836,
          15.150300601202403,
          15.31062124248497,
          15.47094188376753,
          15.631262525050097,
          15.791583166332664,
          15.951903807615231,
          16.11222444889779,
          16.27254509018036,
          16.432865731462925,
          16.593186372745485,
          16.753507014028052,
          16.91382765531062,
          17.074148296593187,
          17.234468937875747,
          17.394789579158314,
          17.55511022044088,
          17.715430861723448,
          17.875751503006008,
          18.036072144288575,
          18.196392785571142,
          18.3567134268537,
          18.51703406813627,
          18.677354709418836,
          18.837675350701403,
          18.997995991983963,
          19.15831663326653,
          19.318637274549097,
          19.478957915831664,
          19.639278557114224,
          19.79959919839679,
          19.95991983967936,
          20.120240480961918,
          20.280561122244485,
          20.440881763527052,
          20.60120240480962,
          20.76152304609218,
          20.921843687374746,
          21.082164328657313,
          21.24248496993988,
          21.40280561122244,
          21.563126252505008,
          21.723446893787575,
          21.883767535070135,
          22.0440881763527,
          22.20440881763527,
          22.364729458917836,
          22.525050100200396,
          22.685370741482963,
          22.84569138276553,
          23.006012024048097,
          23.166332665330657,
          23.326653306613224,
          23.48697394789579,
          23.64729458917835,
          23.807615230460918,
          23.967935871743485,
          24.128256513026045,
          24.288577154308612,
          24.44889779559118,
          24.609218436873746,
          24.769539078156313,
          24.92985971943888,
          25.090180360721433,
          25.250501002004,
          25.410821643286567,
          25.571142284569135,
          25.7314629258517,
          25.89178356713427,
          26.052104208416836,
          26.212424849699403,
          26.372745490981956,
          26.533066132264523,
          26.69338677354709,
          26.853707414829657,
          27.014028056112224,
          27.17434869739479,
          27.334669338677358,
          27.49498997995991,
          27.655310621242478,
          27.815631262525045,
          27.975951903807612,
          28.13627254509018,
          28.296593186372746,
          28.456913827655313,
          28.617234468937866,
          28.777555110220433,
          28.937875751503,
          29.098196392785567,
          29.258517034068134,
          29.4188376753507,
          29.57915831663327,
          29.739478957915836,
          29.89979959919839,
          30.060120240480956,
          30.220440881763523,
          30.38076152304609,
          30.541082164328657,
          30.701402805611224,
          30.86172344689379,
          31.022044088176344,
          31.18236472945891,
          31.342685370741478,
          31.503006012024045,
          31.663326653306612,
          31.82364729458918,
          31.983967935871746,
          32.1442885771543,
          32.304609218436866,
          32.46492985971943,
          32.625250501002,
          32.78557114228457,
          32.945891783567134,
          33.1062124248497,
          33.26653306613227,
          33.42685370741482,
          33.58717434869739,
          33.747494989979955,
          33.90781563126252,
          34.06813627254509,
          34.22845691382766,
          34.388777555110224,
          34.54909819639278,
          34.709418837675344,
          34.86973947895791,
          35.03006012024048,
          35.190380761523045,
          35.35070140280561,
          35.51102204408818,
          35.67134268537073,
          35.8316633266533,
          35.991983967935866,
          36.15230460921843,
          36.312625250501,
          36.47294589178357,
          36.633266533066134,
          36.7935871743487,
          36.953907815631254,
          37.11422845691382,
          37.27454909819639,
          37.434869739478955,
          37.59519038076152,
          37.75551102204409,
          37.91583166332666,
          38.07615230460921,
          38.23647294589178,
          38.39679358717434,
          38.55711422845691,
          38.71743486973948,
          38.877755511022045,
          39.03807615230461,
          39.198396793587165,
          39.35871743486973,
          39.5190380761523,
          39.679358717434866,
          39.83967935871743,
          40
         ],
         "xaxis": "x",
         "y": [
          4800,
          4761.600154216248,
          4723.354524680624,
          4685.2631113931275,
          4647.325914353757,
          4609.542933562515,
          4571.914169019403,
          4534.439620724415,
          4497.119288677555,
          4459.953172878823,
          4422.94127332822,
          4386.0835900257425,
          4349.380122971394,
          4312.830872165173,
          4276.435837607078,
          4240.195019297111,
          4204.108417235271,
          4168.176031421562,
          4132.397861855976,
          4096.77390853852,
          4061.3041714691917,
          4025.9886506479897,
          3990.827346074915,
          3955.8202577499683,
          3920.9673856731506,
          3886.268729844459,
          3851.7242902638945,
          3817.3340669314575,
          3783.0980598471497,
          3749.0162690109682,
          3715.088694422914,
          3681.3153360829865,
          3647.6961939911894,
          3614.2312681475178,
          3580.920558551973,
          3547.764065204558,
          3514.7617881052693,
          3481.9137272541075,
          3449.219882651073,
          3416.6802542961677,
          3384.294842189389,
          3352.0636463307374,
          3319.9866667202145,
          3288.063903357818,
          3256.2953562435487,
          3224.6810253774074,
          3193.2209107593953,
          3161.915012389509,
          3130.7633302677496,
          3099.765864394118,
          3068.922614768616,
          3038.2335813912396,
          3007.6987642619906,
          2977.31816338087,
          2947.0917787478766,
          2917.0196103630105,
          2887.101658226272,
          2857.337922337661,
          2827.7284026971784,
          2798.2730993048217,
          2768.9720121605937,
          2739.825141264493,
          2710.8324866165194,
          2681.994048216674,
          2653.309826064956,
          2624.779820161365,
          2596.4040305059016,
          2568.1824570985655,
          2540.1150999393576,
          2512.201959028277,
          2484.443034365324,
          2456.8383259504985,
          2429.3878337838005,
          2402.0915578652293,
          2374.9494981947864,
          2347.961654772471,
          2321.128027598283,
          2294.448616672222,
          2267.923421994289,
          2241.552443564484,
          2215.335681382806,
          2189.2731354492553,
          2163.3648057638325,
          2137.6106923265374,
          2112.010795137369,
          2086.5651141963285,
          2061.2736495034155,
          2036.1364010586308,
          2011.1533688619725,
          1986.3245529134417,
          1961.6499532130392,
          1937.1295697607643,
          1912.7634025566163,
          1888.551451600596,
          1864.4937168927036,
          1840.5901984329382,
          1816.8408962213,
          1793.2458102577903,
          1769.8049405424076,
          1746.5182870751523,
          1723.385849856025,
          1700.4076288850245,
          1677.5836241621523,
          1654.9138356874068,
          1632.3982634607894,
          1610.0369074822993,
          1587.829767751937,
          1565.776844269702,
          1543.8781370355944,
          1522.1336460496145,
          1500.5433713117618,
          1479.107312822037,
          1457.8254705804395,
          1436.6978445869697,
          1415.724434841627,
          1394.9052413444124,
          1374.2402640953248,
          1353.729503094365,
          1333.372958341533,
          1313.170629836828,
          1293.1225175802508,
          1273.2286215718009,
          1253.488941811479,
          1233.903478299284,
          1214.4722310352167,
          1195.195200019277,
          1176.072385251465,
          1157.10378673178,
          1138.289404460223,
          1119.6292384367937,
          1101.1232886614914,
          1082.771555134317,
          1064.5740378552696,
          1046.5307368243502,
          1028.6416520415582,
          1010.9067835068937,
          993.3261312203565,
          975.8996951819472,
          958.627475391665,
          941.5094718495106,
          924.5456845554838,
          907.7361135095844,
          891.0807587118127,
          874.579620162168,
          858.2326978606513,
          842.0399918072618,
          826.0015020020003,
          810.1172284448655,
          794.3871711358589,
          778.8113300749795,
          763.389705262228,
          748.1222966976038,
          733.0091043811069,
          718.0501283127379,
          703.245368492496,
          688.594824920382,
          674.0984975963952,
          659.7563865205361,
          645.5684916928044,
          631.5348131132005,
          617.655350781724,
          603.9301046983747,
          590.3590748631534,
          576.9422612760592,
          563.6796639370928,
          550.5712828462536,
          537.6171180035424,
          524.8171694089582,
          512.1714370625018,
          499.6799209641728,
          487.3426211139715,
          475.1595375118977,
          463.1306701579513,
          451.2560190521325,
          439.535584194441,
          427.9693655848773,
          416.5573632234409,
          405.2995771101322,
          394.1960072449508,
          383.2466536278972,
          372.4515162589708,
          361.81059513817223,
          351.3238902655011,
          340.9914016409573,
          330.81312926454126,
          320.7890731362525,
          310.9192332560915,
          301.2036096240578,
          291.64220224015173,
          282.23501110437303,
          272.9820362167221,
          263.88327757719844,
          254.93873518580253,
          246.14840904253413,
          237.51229914739304,
          229.03040550037963,
          220.70272810149362,
          212.52926695073523,
          204.51002204810425,
          196.64499339360088,
          188.93418098722512,
          181.37758482897667,
          173.97520491885572,
          166.72704125686263,
          159.63309384299674,
          152.69336267725836,
          145.9078477596475,
          139.27654909016445,
          132.79946666880863,
          126.47660049558036,
          120.30795057047956,
          114.29351689350659,
          108.43329946466085,
          102.72729828394262,
          97.17551335135217,
          91.77794466688898,
          86.53459223055332,
          81.44545604234517,
          76.51053610226478,
          71.72983241031167,
          67.10334496648609,
          62.63107377078802,
          58.31301882321767,
          54.14918012377465,
          50.139557672459134,
          46.28415146927132,
          42.58296151421085,
          39.035987807277905,
          35.64323034847247,
          32.404689137794705,
          29.32036417524432,
          26.390255460821447,
          23.614362994526097,
          20.992686776358383,
          18.52522680631807,
          16.211983084405276,
          14.0529556106201,
          12.048144384962344,
          10.19754940743211,
          8.501170678029396,
          6.959008196754269,
          5.57106196360659,
          4.337331978586434,
          3.2578182416937986,
          2.3325207529287217,
          1.5614395122911222,
          0.944574519781044,
          0.481925775398504,
          0.17349327914346147,
          0.019277031015940162,
          0.006425677005313387,
          0.05783109304781706,
          0.160641925132829,
          0.314858173260348,
          0.5204798374303741,
          0.7775069176428947,
          1.0859394138979328,
          1.4457773261954778,
          1.8570206545355108,
          2.3196693989180677,
          2.833723559343132,
          3.399183135810703,
          4.016048128320753,
          4.684318536873336,
          5.403994361468426,
          6.175075602106023,
          6.997562258786091,
          7.8714543315086996,
          8.796751820273816,
          9.773454725081395,
          10.801563045931523,
          11.881076782824158,
          13.011995935759302,
          14.194320504736897,
          15.428050489757052,
          16.713185890819712,
          18.049726707924883,
          19.437672941072496,
          20.877024590262675,
          22.367781655495364,
          23.909944136770488,
          25.503512034088185,
          27.148485347448393,
          28.844864076851106,
          30.592648222296248,
          32.39183778378398,
          34.242432761314205,
          36.14443315488695,
          38.09783896450211,
          40.102650190159856,
          42.15886683186012,
          44.26648888960279,
          46.425516363388056,
          48.635949253215834,
          50.89778755908612,
          53.21103128099881,
          55.57568041895411,
          57.99173497295191,
          60.45919494299222,
          62.97806032907493,
          65.54833113120024,
          68.17000734936808,
          70.8430889835783,
          73.56757603383114,
          76.34346850012649,
          79.17076638246435,
          82.04946968084458,
          84.97957839526745,
          87.96109252573282,
          90.99401207224071,
          94.07833703479095,
          97.21406741338384,
          100.40120320801925,
          103.639744418697,
          106.92969104541743,
          110.27104308818035,
          113.66380054698577,
          117.10796342183356,
          120.60353171272399,
          124.15050541965694,
          127.74888454263223,
          131.39866908165018,
          135.09985903671065,
          138.85245440781364,
          142.65645519495894,
          146.51186139814692,
          150.41867301737742,
          154.37689005265042,
          158.38651250396575,
          162.44754037132375,
          166.55997365472427,
          170.7238123541671,
          174.93905646965263,
          179.20570600118066,
          183.5237609487512,
          187.89322131236406,
          192.31408709201963,
          196.7863582877177,
          201.31003489945826,
          205.88511692724114,
          210.5116043710667,
          215.1894972309348,
          219.91879550684519,
          224.6994991987983,
          229.53160830679388,
          234.41512283083202,
          239.3500427709124,
          244.33636812703554,
          249.3740988992012,
          254.46323508740932,
          259.60377669165973,
          264.79572371195286,
          270.03907614828853,
          275.33383400066646,
          280.67999726908715,
          286.07756595355033,
          291.526540054056,
          297.026919570604,
          302.5787045031947,
          308.18189485182785,
          313.83649061650357,
          319.54249179722154,
          325.2998983939823,
          331.1087104067855,
          336.96892783563095,
          342.8805506805192,
          348.84357894144995,
          354.85801261842323,
          360.9238517114387,
          367.04109622049697,
          373.20974614559776,
          379.42980148674104,
          385.7012622439266,
          392.0241284171548,
          398.3984000064257,
          404.82407701173867,
          411.3011594330945,
          417.82964727049284,
          424.40954052393363,
          431.0408391934167,
          437.72354327894254,
          444.4576527805109,
          451.24316769812174,
          458.0800880317748,
          464.96841378147064,
          471.90814494720905,
          478.8992815289896,
          485.941823526813,
          493.0357709406789,
          500.18112377058725,
          507.37788201653785,
          514.6260456785312,
          521.9256147565671,
          529.2765892506457,
          536.6789691607662,
          544.1327544869297,
          551.6379452291357,
          559.1945413873838,
          566.8025429616747,
          574.4619499520081,
          582.1727623583838,
          589.9349801808022,
          597.7486034192632,
          605.6136320737667,
          613.5300661443127,
          621.4979056309012,
          629.5171505335315,
          637.5878008522051,
          645.7098565869211,
          653.8833177376796,
          662.1081843044806,
          670.3844562873242,
          678.7121336862102,
          687.0912165011388,
          695.5217047321091,
          704.0035983791226,
          712.5368974421787,
          721.1216019212773,
          729.7577118164184,
          738.4452271276019,
          747.1841478548281,
          755.9744739980958,
          764.816205557407,
          773.7093425327606,
          782.6538849241567,
          791.6498327315954,
          800.6971859550765,
          809.7959445946002,
          818.9461086501656,
          828.1476781217742,
          837.4006530094254,
          846.705033313119,
          856.0608190328552,
          865.4680101686339,
          874.9266067204551,
          884.4366086883188,
          893.9980160722241,
          903.6108288721729,
          913.275047088164,
          922.9906707201977,
          932.7576997682739,
          942.5761342323927,
          952.4459741125539,
          962.3672194087568,
          972.3398701210031,
          982.3639262492918,
          992.4393877936232,
          1002.5662547539969,
          1012.7445271304132,
          1022.974204922872,
          1033.2552881313723,
          1043.5877767559161,
          1053.9716707965024,
          1064.4069702531312,
          1074.8936751258025,
          1085.4317854145163,
          1096.0213011192727,
          1106.6622222400715,
          1117.354548776912,
          1128.0982807297958,
          1138.8934180987221,
          1149.739960883691,
          1160.6379090847024,
          1171.5872627017563,
          1182.5880217348526,
          1193.6401861839906,
          1204.743756049172,
          1215.898731330396,
          1227.1051120276622,
          1238.3628981409713,
          1249.6720896703227,
          1261.0326866157166,
          1272.444688977152,
          1283.908096754631,
          1295.4229099481524,
          1306.9891285577164,
          1318.6067525833228,
          1330.2757820249717,
          1341.9962168826632,
          1353.7680571563972,
          1365.5913028461728,
          1377.4659539519917,
          1389.3920104738531,
          1401.3694724117572,
          1413.3983397657037,
          1425.4786125356927,
          1437.6102907217244,
          1449.7933743237973,
          1462.0278633419136,
          1474.3137577760729,
          1486.6510576262745,
          1499.0397628925184,
          1511.479873574805,
          1523.9713896731341,
          1536.5143111875045,
          1549.1086381179186,
          1561.7543704643751,
          1574.4515082268742,
          1587.200051405416,
          1600
         ],
         "yaxis": "y"
        }
       ],
       "layout": {
        "height": 250,
        "legend": {
         "tracegroupgap": 0
        },
        "margin": {
         "t": 30
        },
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "rgb(36,36,36)"
            },
            "error_y": {
             "color": "rgb(36,36,36)"
            },
            "marker": {
             "line": {
              "color": "white",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "white",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "rgb(36,36,36)",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "rgb(36,36,36)"
            },
            "baxis": {
             "endlinecolor": "rgb(36,36,36)",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "rgb(36,36,36)"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "line": {
              "color": "white",
              "width": 0.6
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "parcoords"
           }
          ],
          "pie": [
           {
            "automargin": true,
            "type": "pie"
           }
          ],
          "scatter": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "rgb(237,237,237)"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "rgb(217,217,217)"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "autosize": true,
          "autotypenumbers": "strict",
          "coloraxis": {
           "colorbar": {
            "outlinewidth": 1,
            "tickcolor": "rgb(36,36,36)",
            "ticks": "outside"
           }
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "rgb(103,0,31)"
            ],
            [
             0.1,
             "rgb(178,24,43)"
            ],
            [
             0.2,
             "rgb(214,96,77)"
            ],
            [
             0.3,
             "rgb(244,165,130)"
            ],
            [
             0.4,
             "rgb(253,219,199)"
            ],
            [
             0.5,
             "rgb(247,247,247)"
            ],
            [
             0.6,
             "rgb(209,229,240)"
            ],
            [
             0.7,
             "rgb(146,197,222)"
            ],
            [
             0.8,
             "rgb(67,147,195)"
            ],
            [
             0.9,
             "rgb(33,102,172)"
            ],
            [
             1,
             "rgb(5,48,97)"
            ]
           ],
           "sequential": [
            [
             0,
             "#440154"
            ],
            [
             0.1111111111111111,
             "#482878"
            ],
            [
             0.2222222222222222,
             "#3e4989"
            ],
            [
             0.3333333333333333,
             "#31688e"
            ],
            [
             0.4444444444444444,
             "#26828e"
            ],
            [
             0.5555555555555556,
             "#1f9e89"
            ],
            [
             0.6666666666666666,
             "#35b779"
            ],
            [
             0.7777777777777778,
             "#6ece58"
            ],
            [
             0.8888888888888888,
             "#b5de2b"
            ],
            [
             1,
             "#fde725"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#440154"
            ],
            [
             0.1111111111111111,
             "#482878"
            ],
            [
             0.2222222222222222,
             "#3e4989"
            ],
            [
             0.3333333333333333,
             "#31688e"
            ],
            [
             0.4444444444444444,
             "#26828e"
            ],
            [
             0.5555555555555556,
             "#1f9e89"
            ],
            [
             0.6666666666666666,
             "#35b779"
            ],
            [
             0.7777777777777778,
             "#6ece58"
            ],
            [
             0.8888888888888888,
             "#b5de2b"
            ],
            [
             1,
             "#fde725"
            ]
           ]
          },
          "colorway": [
           "#1F77B4",
           "#FF7F0E",
           "#2CA02C",
           "#D62728",
           "#9467BD",
           "#8C564B",
           "#E377C2",
           "#7F7F7F",
           "#BCBD22",
           "#17BECF"
          ],
          "font": {
           "color": "rgb(36,36,36)"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "white",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "height": 250,
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "margin": {
           "b": 10,
           "l": 10,
           "r": 10,
           "t": 10
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "white",
          "polar": {
           "angularaxis": {
            "gridcolor": "rgb(232,232,232)",
            "linecolor": "rgb(36,36,36)",
            "showgrid": false,
            "showline": true,
            "ticks": "outside"
           },
           "bgcolor": "white",
           "radialaxis": {
            "gridcolor": "rgb(232,232,232)",
            "linecolor": "rgb(36,36,36)",
            "showgrid": false,
            "showline": true,
            "ticks": "outside"
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "white",
            "gridcolor": "rgb(232,232,232)",
            "gridwidth": 2,
            "linecolor": "rgb(36,36,36)",
            "showbackground": true,
            "showgrid": false,
            "showline": true,
            "ticks": "outside",
            "zeroline": false,
            "zerolinecolor": "rgb(36,36,36)"
           },
           "yaxis": {
            "backgroundcolor": "white",
            "gridcolor": "rgb(232,232,232)",
            "gridwidth": 2,
            "linecolor": "rgb(36,36,36)",
            "showbackground": true,
            "showgrid": false,
            "showline": true,
            "ticks": "outside",
            "zeroline": false,
            "zerolinecolor": "rgb(36,36,36)"
           },
           "zaxis": {
            "backgroundcolor": "white",
            "gridcolor": "rgb(232,232,232)",
            "gridwidth": 2,
            "linecolor": "rgb(36,36,36)",
            "showbackground": true,
            "showgrid": false,
            "showline": true,
            "ticks": "outside",
            "zeroline": false,
            "zerolinecolor": "rgb(36,36,36)"
           }
          },
          "shapedefaults": {
           "fillcolor": "black",
           "line": {
            "width": 0
           },
           "opacity": 0.3
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "rgb(232,232,232)",
            "linecolor": "rgb(36,36,36)",
            "showgrid": false,
            "showline": true,
            "ticks": "outside"
           },
           "baxis": {
            "gridcolor": "rgb(232,232,232)",
            "linecolor": "rgb(36,36,36)",
            "showgrid": false,
            "showline": true,
            "ticks": "outside"
           },
           "bgcolor": "white",
           "caxis": {
            "gridcolor": "rgb(232,232,232)",
            "linecolor": "rgb(36,36,36)",
            "showgrid": false,
            "showline": true,
            "ticks": "outside"
           }
          },
          "title": {
           "x": 0.5,
           "xanchor": "center"
          },
          "width": 350,
          "xaxis": {
           "automargin": true,
           "gridcolor": "rgb(232,232,232)",
           "linecolor": "rgb(36,36,36)",
           "showgrid": true,
           "showline": true,
           "ticks": "outside",
           "title": {
            "standoff": 15
           },
           "zeroline": false,
           "zerolinecolor": "rgb(36,36,36)"
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "rgb(232,232,232)",
           "linecolor": "rgb(36,36,36)",
           "showgrid": true,
           "showline": true,
           "ticks": "outside",
           "title": {
            "standoff": 15
           },
           "zeroline": false,
           "zerolinecolor": "rgb(36,36,36)"
          }
         }
        },
        "title": {
         "text": "Modified quadratic loss"
        },
        "width": 350,
        "xaxis": {
         "anchor": "y",
         "autorange": true,
         "domain": [
          0,
          1
         ],
         "range": [
          -40,
          40
         ],
         "title": {
          "text": "Relative error (%)"
         },
         "type": "linear"
        },
        "yaxis": {
         "anchor": "x",
         "autorange": true,
         "domain": [
          0,
          1
         ],
         "range": [
          -266.65988400760557,
          5066.6663096846105
         ],
         "title": {
          "text": "Loss"
         },
         "type": "linear"
        }
       }
      },
      "image/png": "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",
      "image/svg+xml": [
       "<svg class=\"main-svg\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"350\" height=\"250\" style=\"\" viewBox=\"0 0 350 250\"><rect x=\"0\" y=\"0\" width=\"350\" height=\"250\" style=\"fill: rgb(255, 255, 255); fill-opacity: 1;\"/><defs id=\"defs-e3af1f\"><g class=\"clips\"><clipPath id=\"clipe3af1fxyplot\" class=\"plotclip\"><rect width=\"262\" height=\"161\"/></clipPath><clipPath class=\"axesclip\" id=\"clipe3af1fx\"><rect x=\"71\" y=\"0\" width=\"262\" height=\"250\"/></clipPath><clipPath class=\"axesclip\" id=\"clipe3af1fy\"><rect x=\"0\" y=\"30\" width=\"350\" height=\"161\"/></clipPath><clipPath class=\"axesclip\" id=\"clipe3af1fxy\"><rect x=\"71\" y=\"30\" width=\"262\" height=\"161\"/></clipPath></g><g class=\"gradients\"/><g class=\"patterns\"/></defs><g class=\"bglayer\"/><g class=\"layer-below\"><g class=\"imagelayer\"/><g class=\"shapelayer\"/></g><g class=\"cartesianlayer\"><g class=\"subplot xy\"><g class=\"layer-subplot\"><g class=\"shapelayer\"/><g class=\"imagelayer\"/></g><g class=\"gridlayer\"><g class=\"x\"><path class=\"xgrid crisp\" transform=\"translate(136.5,0)\" d=\"M0,30v161\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"xgrid crisp\" transform=\"translate(202,0)\" d=\"M0,30v161\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"xgrid crisp\" transform=\"translate(267.5,0)\" d=\"M0,30v161\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/></g><g class=\"y\"><path class=\"ygrid crisp\" transform=\"translate(0,182.95)\" d=\"M71,0h262\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"ygrid crisp\" transform=\"translate(0,122.58)\" d=\"M71,0h262\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"ygrid crisp\" transform=\"translate(0,62.2)\" d=\"M71,0h262\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/></g></g><g class=\"zerolinelayer\"/><path class=\"xlines-below\"/><path class=\"ylines-below\"/><g class=\"overlines-below\"/><g class=\"xaxislayer-below\"/><g class=\"yaxislayer-below\"/><g class=\"overaxes-below\"/><g class=\"plot\" transform=\"translate(71,30)\" clip-path=\"url(#clipe3af1fxyplot)\"><g class=\"scatterlayer mlayer\"><g class=\"trace scatter trace1403d4\" style=\"stroke-miterlimit: 2; opacity: 1;\"><g class=\"fills\"/><g class=\"errorbars\"/><g class=\"lines\"><path class=\"js-line\" d=\"M0,8.05L15.75,40.8L16.28,41.82L28.88,64.89L29.4,65.8L44.63,89.96L45.15,90.73L59.33,109.58L59.86,110.21L70.88,122.43L71.41,122.96L81.91,132.6L82.43,133.03L93.46,141.05L93.98,141.38L103.96,146.78L104.48,147.01L113.94,150.49L114.46,150.64L124.44,152.59L124.96,152.64L135.46,152.89L135.99,152.88L153.84,151.48L154.36,151.41L170.64,148.53L171.17,148.41L188.49,143.65L189.02,143.48L208.97,135.84L209.49,135.61L224.72,128.23L225.25,127.95L243.62,117.25L244.15,116.92L262,104.65\" style=\"vector-effect: non-scaling-stroke; fill: none; stroke: rgb(31, 119, 180); stroke-opacity: 1; stroke-width: 2px; opacity: 1;\"/></g><g class=\"points\"/><g class=\"text\"/></g></g></g><g class=\"overplot\"/><path class=\"xlines-above crisp\" d=\"M70,191.5H333\" style=\"fill: none; stroke-width: 1px; stroke: rgb(36, 36, 36); stroke-opacity: 1;\"/><path class=\"ylines-above crisp\" d=\"M70.5,30V191\" style=\"fill: none; stroke-width: 1px; stroke: rgb(36, 36, 36); stroke-opacity: 1;\"/><g class=\"overlines-above\"/><g class=\"xaxislayer-above\"><path class=\"xtick ticks crisp\" d=\"M0,192v5\" transform=\"translate(71,0)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"xtick ticks crisp\" d=\"M0,192v5\" transform=\"translate(136.5,0)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"xtick ticks crisp\" d=\"M0,192v5\" transform=\"translate(202,0)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"xtick ticks crisp\" d=\"M0,192v5\" transform=\"translate(267.5,0)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"xtick ticks crisp\" d=\"M0,192v5\" transform=\"translate(333,0)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><g class=\"xtick\"><text text-anchor=\"middle\" x=\"0\" y=\"211.4\" transform=\"translate(71,0)\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\">−40</text></g><g class=\"xtick\"><text text-anchor=\"middle\" x=\"0\" y=\"211.4\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(136.5,0)\">−20</text></g><g class=\"xtick\"><text text-anchor=\"middle\" x=\"0\" y=\"211.4\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(202,0)\">0</text></g><g class=\"xtick\"><text text-anchor=\"middle\" x=\"0\" y=\"211.4\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(267.5,0)\">20</text></g><g class=\"xtick\"><text text-anchor=\"middle\" x=\"0\" y=\"211.4\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(333,0)\">40</text></g></g><g class=\"yaxislayer-above\"><path class=\"ytick ticks crisp\" d=\"M70,0h-5\" transform=\"translate(0,182.95)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"ytick ticks crisp\" d=\"M70,0h-5\" transform=\"translate(0,122.58)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"ytick ticks crisp\" d=\"M70,0h-5\" transform=\"translate(0,62.2)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><g class=\"ytick\"><text text-anchor=\"end\" x=\"62.6\" y=\"4.199999999999999\" transform=\"translate(0,182.95)\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\">0</text></g><g class=\"ytick\"><text text-anchor=\"end\" x=\"62.6\" y=\"4.199999999999999\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(0,122.58)\">2000</text></g><g class=\"ytick\"><text text-anchor=\"end\" x=\"62.6\" y=\"4.199999999999999\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(0,62.2)\">4000</text></g></g><g class=\"overaxes-above\"/></g></g><g class=\"polarlayer\"/><g class=\"smithlayer\"/><g class=\"ternarylayer\"/><g class=\"geolayer\"/><g class=\"funnelarealayer\"/><g class=\"pielayer\"/><g class=\"iciclelayer\"/><g class=\"treemaplayer\"/><g class=\"sunburstlayer\"/><g class=\"glimages\"/><defs id=\"topdefs-e3af1f\"><g class=\"clips\"/></defs><g class=\"layer-above\"><g class=\"imagelayer\"/><g class=\"shapelayer\"/></g><g class=\"infolayer\"><g class=\"g-gtitle\"><text class=\"gtitle\" x=\"175\" y=\"15\" text-anchor=\"middle\" dy=\"0em\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 17px; fill: rgb(36, 36, 36); opacity: 1; font-weight: normal; white-space: pre;\">Modified quadratic loss</text></g><g class=\"g-xtitle\"><text class=\"xtitle\" x=\"202\" y=\"239.70625\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(36, 36, 36); opacity: 1; font-weight: normal; white-space: pre;\">Relative error (%)</text></g><g class=\"g-ytitle\" transform=\"translate(4.6591796875,0)\"><text class=\"ytitle\" transform=\"rotate(-90,10.340625000000003,110.5)\" x=\"10.340625000000003\" y=\"110.5\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(36, 36, 36); opacity: 1; font-weight: normal; white-space: pre;\">Loss</text></g></g></svg>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xs = np.linspace(-40, 40, 500)\n",
    "loss = anes_loss(xs)\n",
    "\n",
    "fig = px.line(x=xs, y=loss, title='Modified quadratic loss',\n",
    "              width=350, height=250)\n",
    "\n",
    "margin(fig, t=30)\n",
    "xlabel(fig, 'Relative error (%)')\n",
    "ylabel(fig, 'Loss')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that a value of –10 on the x-axis reflects an overestimate of 10%.\n",
    "\n",
    "Next, let's fit a simple linear model using this loss function."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fitting a Simple Linear Model\n",
    "\n",
    "We saw that girth has the highest correlation with weight among the donkeys in our train set. So we fit a model of the form: \n",
    "\n",
    "$$\n",
    "\\theta_0 + \\theta_1 \\text{Girth}\n",
    "$$\n",
    "\n",
    "To find the best fit $\\theta_0$ and $\\theta_1$ to the data, we first\n",
    "create a design matrix that has girth and an intercept term.\n",
    "We also create the $y$ vector of observed donkey weights:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>intr</th>\n",
       "      <th>Girth</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>230</th>\n",
       "      <td>1</td>\n",
       "      <td>116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>1</td>\n",
       "      <td>117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>354</th>\n",
       "      <td>1</td>\n",
       "      <td>123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>1</td>\n",
       "      <td>123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>1</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>381</th>\n",
       "      <td>1</td>\n",
       "      <td>106</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>433 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     intr  Girth\n",
       "230     1    116\n",
       "74      1    117\n",
       "354     1    123\n",
       "..    ...    ...\n",
       "157     1    123\n",
       "41      1    103\n",
       "381     1    106\n",
       "\n",
       "[433 rows x 2 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = train_set.assign(intr=1)[['intr', 'Girth']]\n",
    "y = train_set['Weight']\n",
    "X"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we want to find the $\\theta_0$ and $\\theta_1$ that minimize the average anesthetic loss over the data. To do this, we could use calculus as we did in\n",
    "{numref}`Chapter %s <ch:linear>`, but here we'll instead use the `minimize` method from the `scipy` package, which performs a numerical optimization (see {numref}`Chapter %s <ch:gd>`):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from scipy.optimize import minimize\n",
    "\n",
    "def training_loss(X, y):\n",
    "    def loss(theta):\n",
    "        predicted = X @ theta\n",
    "        return np.mean(anes_loss(100 * (y - predicted) / predicted))\n",
    "    return loss\n",
    "\n",
    "results = minimize(training_loss(X, y), np.ones(2))\n",
    "theta_hat = results['x']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "After fitting:\n",
      "θ₀ = -218.51\n",
      "θ₁ =    3.16\n"
     ]
    }
   ],
   "source": [
    "print('After fitting:')\n",
    "print(f'θ₀ = {theta_hat[0]:>7.2f}')\n",
    "print(f'θ₁ = {theta_hat[1]:>7.2f}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's see how this simple model does. We can use the model to predict the\n",
    "donkey weights on our train set, then find the errors in the predictions.\n",
    "The residual plot that follows shows the model error as a percentage of the predicted\n",
    "value. It's more important for the prediction errors to be small relative to\n",
    "the size of the donkey, since a 10 kg error is much worse for a 100 kg\n",
    "donkey than a 200 kg one. Thus, we find the relative error of each prediction:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "predicted = X @ theta_hat\n",
    "resids = 100 * (y - predicted) / predicted"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's examine a scatter plot of the relative errors:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "hovertemplate": "Predicted weight (kg)=%{x}<br>Percent error=%{y}<extra></extra>",
         "legendgroup": "",
         "marker": {
          "color": "#1F77B4",
          "symbol": "circle"
         },
         "mode": "markers",
         "name": "",
         "orientation": "v",
         "showlegend": false,
         "type": "scatter",
         "x": [
          148.19091880181375,
          151.3521213549619,
          170.3193366738507,
          132.3849060360731,
          170.3193366738507,
          167.15813412070256,
          145.0297162486656,
          176.64174178014693,
          116.57889327033237,
          116.57889327033237,
          116.57889327033237,
          138.70731114236932,
          119.74009582348052,
          141.86851369551746,
          163.9969315675544,
          148.19091880181375,
          148.19091880181375,
          135.54610858922118,
          157.67452646125813,
          141.86851369551746,
          148.19091880181375,
          154.51332390810998,
          154.51332390810998,
          163.9969315675544,
          154.51332390810998,
          75.48326007940662,
          160.83572901440627,
          170.3193366738507,
          116.57889327033237,
          135.54610858922118,
          154.51332390810998,
          154.51332390810998,
          151.3521213549619,
          157.67452646125813,
          160.83572901440627,
          157.67452646125813,
          176.64174178014693,
          135.54610858922118,
          138.70731114236932,
          154.51332390810998,
          157.67452646125813,
          148.19091880181375,
          129.22370348292495,
          132.3849060360731,
          148.19091880181375,
          157.67452646125813,
          154.51332390810998,
          176.64174178014693,
          186.12534943959136,
          145.0297162486656,
          145.0297162486656,
          157.67452646125813,
          170.3193366738507,
          113.41769071718423,
          170.3193366738507,
          170.3193366738507,
          160.83572901440627,
          176.64174178014693,
          135.54610858922118,
          173.48053922699884,
          141.86851369551746,
          132.3849060360731,
          167.15813412070256,
          145.0297162486656,
          97.61167795144357,
          157.67452646125813,
          148.19091880181375,
          148.19091880181375,
          170.3193366738507,
          148.19091880181375,
          173.48053922699884,
          148.19091880181375,
          119.74009582348052,
          163.9969315675544,
          141.86851369551746,
          176.64174178014693,
          182.96414688644322,
          167.15813412070256,
          141.86851369551746,
          148.19091880181375,
          167.15813412070256,
          145.0297162486656,
          141.86851369551746,
          141.86851369551746,
          65.99965241996225,
          116.57889327033237,
          135.54610858922118,
          97.61167795144357,
          141.86851369551746,
          167.15813412070256,
          160.83572901440627,
          163.9969315675544,
          160.83572901440627,
          167.15813412070256,
          132.3849060360731,
          170.3193366738507,
          160.83572901440627,
          135.54610858922118,
          148.19091880181375,
          160.83572901440627,
          97.61167795144357,
          160.83572901440627,
          100.77288050459171,
          170.3193366738507,
          138.70731114236932,
          113.41769071718423,
          167.15813412070256,
          160.83572901440627,
          148.19091880181375,
          151.3521213549619,
          173.48053922699884,
          154.51332390810998,
          145.0297162486656,
          173.48053922699884,
          160.83572901440627,
          170.3193366738507,
          186.12534943959136,
          138.70731114236932,
          170.3193366738507,
          198.77015965218388,
          179.80294433329507,
          176.64174178014693,
          163.9969315675544,
          138.70731114236932,
          148.19091880181375,
          173.48053922699884,
          129.22370348292495,
          138.70731114236932,
          141.86851369551746,
          163.9969315675544,
          163.9969315675544,
          148.19091880181375,
          148.19091880181375,
          173.48053922699884,
          132.3849060360731,
          145.0297162486656,
          138.70731114236932,
          154.51332390810998,
          154.51332390810998,
          132.3849060360731,
          189.2865519927395,
          81.8056651857029,
          145.0297162486656,
          148.19091880181375,
          129.22370348292495,
          132.3849060360731,
          145.0297162486656,
          138.70731114236932,
          195.6089570990358,
          65.99965241996225,
          170.3193366738507,
          110.25648816403614,
          135.54610858922118,
          148.19091880181375,
          173.48053922699884,
          151.3521213549619,
          145.0297162486656,
          157.67452646125813,
          113.41769071718423,
          154.51332390810998,
          88.1280702919992,
          160.83572901440627,
          132.3849060360731,
          113.41769071718423,
          148.19091880181375,
          135.54610858922118,
          138.70731114236932,
          122.90129837662866,
          110.25648816403614,
          157.67452646125813,
          141.86851369551746,
          145.0297162486656,
          132.3849060360731,
          163.9969315675544,
          148.19091880181375,
          154.51332390810998,
          154.51332390810998,
          157.67452646125813,
          81.8056651857029,
          163.9969315675544,
          186.12534943959136,
          154.51332390810998,
          103.93408305773985,
          160.83572901440627,
          122.90129837662866,
          167.15813412070256,
          167.15813412070256,
          126.0625009297768,
          103.93408305773985,
          151.3521213549619,
          126.0625009297768,
          148.19091880181375,
          141.86851369551746,
          154.51332390810998,
          205.09256475848017,
          160.83572901440627,
          138.70731114236932,
          135.54610858922118,
          116.57889327033237,
          154.51332390810998,
          160.83572901440627,
          81.8056651857029,
          81.8056651857029,
          141.86851369551746,
          167.15813412070256,
          154.51332390810998,
          84.96686773885105,
          148.19091880181375,
          145.0297162486656,
          189.2865519927395,
          145.0297162486656,
          167.15813412070256,
          151.3521213549619,
          151.3521213549619,
          135.54610858922118,
          163.9969315675544,
          138.70731114236932,
          135.54610858922118,
          107.095285610888,
          179.80294433329507,
          132.3849060360731,
          176.64174178014693,
          145.0297162486656,
          170.3193366738507,
          157.67452646125813,
          141.86851369551746,
          157.67452646125813,
          163.9969315675544,
          160.83572901440627,
          157.67452646125813,
          173.48053922699884,
          97.61167795144357,
          176.64174178014693,
          151.3521213549619,
          145.0297162486656,
          170.3193366738507,
          151.3521213549619,
          179.80294433329507,
          148.19091880181375,
          170.3193366738507,
          132.3849060360731,
          160.83572901440627,
          135.54610858922118,
          160.83572901440627,
          151.3521213549619,
          135.54610858922118,
          138.70731114236932,
          157.67452646125813,
          145.0297162486656,
          148.19091880181375,
          132.3849060360731,
          141.86851369551746,
          148.19091880181375,
          176.64174178014693,
          167.15813412070256,
          148.19091880181375,
          145.0297162486656,
          160.83572901440627,
          173.48053922699884,
          154.51332390810998,
          189.2865519927395,
          148.19091880181375,
          113.41769071718423,
          138.70731114236932,
          160.83572901440627,
          122.90129837662866,
          163.9969315675544,
          145.0297162486656,
          141.86851369551746,
          182.96414688644322,
          154.51332390810998,
          148.19091880181375,
          157.67452646125813,
          154.51332390810998,
          179.80294433329507,
          148.19091880181375,
          135.54610858922118,
          151.3521213549619,
          122.90129837662866,
          151.3521213549619,
          163.9969315675544,
          132.3849060360731,
          141.86851369551746,
          145.0297162486656,
          148.19091880181375,
          154.51332390810998,
          154.51332390810998,
          176.64174178014693,
          148.19091880181375,
          122.90129837662866,
          145.0297162486656,
          160.83572901440627,
          154.51332390810998,
          116.57889327033237,
          160.83572901440627,
          129.22370348292495,
          154.51332390810998,
          157.67452646125813,
          157.67452646125813,
          167.15813412070256,
          145.0297162486656,
          138.70731114236932,
          163.9969315675544,
          179.80294433329507,
          160.83572901440627,
          132.3849060360731,
          154.51332390810998,
          116.57889327033237,
          157.67452646125813,
          186.12534943959136,
          138.70731114236932,
          141.86851369551746,
          129.22370348292495,
          163.9969315675544,
          135.54610858922118,
          176.64174178014693,
          182.96414688644322,
          179.80294433329507,
          145.0297162486656,
          151.3521213549619,
          151.3521213549619,
          135.54610858922118,
          141.86851369551746,
          167.15813412070256,
          154.51332390810998,
          154.51332390810998,
          151.3521213549619,
          138.70731114236932,
          135.54610858922118,
          145.0297162486656,
          145.0297162486656,
          151.3521213549619,
          170.3193366738507,
          170.3193366738507,
          122.90129837662866,
          157.67452646125813,
          119.74009582348052,
          138.70731114236932,
          141.86851369551746,
          129.22370348292495,
          157.67452646125813,
          135.54610858922118,
          138.70731114236932,
          157.67452646125813,
          148.19091880181375,
          160.83572901440627,
          138.70731114236932,
          148.19091880181375,
          157.67452646125813,
          154.51332390810998,
          126.0625009297768,
          167.15813412070256,
          145.0297162486656,
          163.9969315675544,
          138.70731114236932,
          135.54610858922118,
          163.9969315675544,
          145.0297162486656,
          110.25648816403614,
          157.67452646125813,
          160.83572901440627,
          160.83572901440627,
          192.44775454588765,
          163.9969315675544,
          119.74009582348052,
          141.86851369551746,
          163.9969315675544,
          100.77288050459171,
          97.61167795144357,
          122.90129837662866,
          145.0297162486656,
          148.19091880181375,
          160.83572901440627,
          126.0625009297768,
          173.48053922699884,
          100.77288050459171,
          132.3849060360731,
          141.86851369551746,
          157.67452646125813,
          132.3849060360731,
          167.15813412070256,
          141.86851369551746,
          163.9969315675544,
          122.90129837662866,
          145.0297162486656,
          135.54610858922118,
          170.3193366738507,
          205.09256475848017,
          167.15813412070256,
          176.64174178014693,
          145.0297162486656,
          91.28927284514728,
          145.0297162486656,
          148.19091880181375,
          119.74009582348052,
          157.67452646125813,
          135.54610858922118,
          163.9969315675544,
          151.3521213549619,
          176.64174178014693,
          119.74009582348052,
          170.3193366738507,
          170.3193366738507,
          170.3193366738507,
          116.57889327033237,
          129.22370348292495,
          151.3521213549619,
          145.0297162486656,
          135.54610858922118,
          151.3521213549619,
          110.25648816403614,
          154.51332390810998,
          160.83572901440627,
          151.3521213549619,
          132.3849060360731,
          176.64174178014693,
          138.70731114236932,
          141.86851369551746,
          157.67452646125813,
          145.0297162486656,
          151.3521213549619,
          160.83572901440627,
          157.67452646125813,
          173.48053922699884,
          129.22370348292495,
          145.0297162486656,
          132.3849060360731,
          151.3521213549619,
          160.83572901440627,
          97.61167795144357,
          170.3193366738507,
          107.095285610888,
          116.57889327033237
         ],
         "xaxis": "x",
         "y": [
          11.342855104816664,
          0.4280604984178936,
          1.5739042779872836,
          8.018356685643937,
          1.5739042779872836,
          3.49481400353459,
          -0.02048976543169728,
          8.694580377818268,
          2.934585012515511,
          -3.069932446547894,
          -7.35887348873604,
          5.25760956475139,
          -19.826354455635222,
          -8.3658546821672,
          5.489778586946915,
          4.594803280282321,
          7.2940240100960585,
          1.0726175955260426,
          9.08547110319799,
          -6.251220559447982,
          -4.177664091612326,
          -10.04012049946958,
          13.906034475491754,
          4.2702435743810545,
          2.903747054563574,
          -1.965018572126144,
          3.8326502595959817,
          0.3996394886463901,
          -18.51012019842522,
          12.138962587736923,
          16.494807986298387,
          1.6093602991602587,
          3.731615120076377,
          5.280163971691083,
          -10.467654865977119,
          12.256560379453745,
          -0.9294189264677235,
          -1.878407735730192,
          0.9319543771588668,
          -7.45134698866295,
          0.8406389849330254,
          5.944413645189189,
          -3.268520688608068,
          -0.2907476747902126,
          7.968829192549493,
          9.08547110319799,
          17.14200136400004,
          1.9011691042046273,
          14.439006100633835,
          -14.500280902851935,
          -2.089031356491731,
          7.817035392695688,
          7.445228224691752,
          -11.83033319788028,
          9.793757803373538,
          -1.3617576953649502,
          -0.5196165177523531,
          -6.590594987812426,
          1.0726175955260426,
          -3.735600117382085,
          5.7317061359609225,
          1.2199985725614508,
          9.477173194490346,
          -0.02048976543169728,
          12.69143437398847,
          -1.062014580820428,
          3.9199980978288864,
          -1.4784433617985882,
          -2.5360224847058435,
          -6.876884821426063,
          -7.1942013107695555,
          13.367270652176968,
          1.8873412126302362,
          -9.144641563843408,
          12.780486545024985,
          7.562345165549328,
          4.938592214552772,
          1.7001062462478627,
          -9.775610763980012,
          7.2940240100960585,
          4.691285841725741,
          3.4270795530016924,
          -4.136586436728764,
          19.829266954089046,
          16.667281079060036,
          -1.3543560296726351,
          3.2858865939682187,
          4.495693692243853,
          -8.3658546821672,
          5.289521760821317,
          0.10213587901169474,
          9.148383624644497,
          11.293679020764554,
          12.468352789968224,
          -0.2907476747902126,
          11.555154987384878,
          12.53718381429265,
          -6.304945732614544,
          6.619218827642624,
          0.10213587901169474,
          -3.700046989500763,
          10.05017422723646,
          -6.720935702818483,
          7.445228224691752,
          0.9319543771588668,
          1.3951168224376755,
          -0.6928374301344399,
          2.589145466067886,
          6.619218827642624,
          9.01730251472995,
          8.945937591705304,
          -2.2737999670496873,
          7.5641627351217595,
          -0.8534324562258602,
          1.3456406725397903,
          -6.0588168527285235,
          14.976278429744792,
          8.141379689813071,
          3.9224338566690706,
          2.631099334511533,
          1.778088606145762,
          1.335051498070157,
          7.928848612078636,
          4.536667033485969,
          2.570387732922018,
          -11.805669568619516,
          -5.590076192081475,
          -2.6727582791682356,
          5.7317061359609225,
          8.538616118361567,
          -4.266501513579968,
          6.619218827642624,
          3.9199980978288864,
          0.2994346082366298,
          -4.822986416845203,
          -11.052711584418546,
          5.25760956475139,
          11.964454342386782,
          8.081294076176835,
          4.241491067264778,
          13.056103430004068,
          10.016830491745955,
          2.0480518256283364,
          2.570387732922018,
          3.696145821812151,
          4.9968641909406095,
          10.32221818986847,
          -4.835585872964497,
          -1.3337615709054111,
          -1.5146328553389334,
          2.16103667265773,
          -3.86053304881566,
          -2.6161640685442507,
          1.8955825504685835,
          17.592440575173978,
          10.338724363393343,
          -1.399517492805053,
          14.79343180045835,
          0.5134201544164785,
          4.1981338099668895,
          0.9893893116141058,
          5.697907449888125,
          11.795222304023095,
          1.3951168224376755,
          7.968829192549493,
          -4.829433066986427,
          3.094781970955128,
          -3.987995604089328,
          -7.4884374620679,
          5.280163971691083,
          1.5024378905224853,
          6.874648871435082,
          9.5291029329956,
          9.148383624644497,
          3.245192915375452,
          -1.6266065893480297,
          -5.509766855557976,
          5.280163971691083,
          5.1271935810016895,
          9.148383624644497,
          -4.902797747360617,
          12.611647720088438,
          1.0255701603370881,
          2.589145466067886,
          -7.242639820899859,
          -1.2910733492300155,
          -0.6928374301344399,
          -15.121468152052275,
          -5.709467850352051,
          -10.80402521522095,
          -7.982152389140785,
          9.318439557456362,
          -13.300000968512043,
          3.550940432265232,
          12.14448474563238,
          0.7238882757757426,
          3.8157245022205486,
          6.236911925224454,
          0.3612203872026234,
          10.670067586983466,
          1.9673930693038382,
          10.016830491745955,
          5.1271935810016895,
          6.436584176867329,
          1.7001062462478627,
          1.6093602991602587,
          10.631358435987813,
          -8.226495186332931,
          19.285898417795284,
          -13.887173555651108,
          -2.778545220178409,
          -6.675196621090198,
          -4.196915971903983,
          0.4280604984178936,
          9.925693589294749,
          2.440941055532264,
          3.8157245022205486,
          10.663449922108807,
          24.18847313525289,
          -10.457528603336241,
          -4.067613293169371,
          12.65740362075956,
          -11.052711584418546,
          3.9224338566690706,
          13.524996089956048,
          8.551218299586548,
          4.645946116439932,
          4.2702435743810545,
          5.697907449888125,
          -1.062014580820428,
          2.60516873716161,
          29.082915737477702,
          3.5995219226080377,
          -12.78615798821604,
          -0.02048976543169728,
          -0.18749290602405663,
          8.356591590398253,
          -9.345199766110605,
          6.619218827642624,
          8.032360619362198,
          17.08283416975392,
          -8.602397675684974,
          2.54813026115416,
          -5.4936356918647355,
          -2.8754941232405895,
          4.761399259596336,
          2.3738394396897076,
          4.645946116439932,
          6.874648871435082,
          7.968829192549493,
          1.2199985725614508,
          2.2073159314288917,
          4.594803280282321,
          14.35575643916297,
          13.066588709063799,
          14.716881017083837,
          -6.226114538611799,
          10.671926624000507,
          6.063769930549079,
          2.2565536768619165,
          -8.604178068267741,
          -3.502858909158891,
          7.566993498586056,
          -4.835585872964497,
          -3.0066261048085443,
          -4.801656658291961,
          6.099546093229845,
          8.943190462495116,
          3.617072013241704,
          -1.073514631072647,
          0.3149735437569433,
          3.9199980978288864,
          0.20642112968187426,
          -6.804153610961292,
          -2.671226742756785,
          2.570387732922018,
          1.8103739283401015,
          7.03516974173486,
          -14.565589308723556,
          -8.161181517894164,
          -3.6567340072970373,
          -1.801493922141876,
          1.5024378905224853,
          -8.294656129671834,
          -2.1532485442520226,
          -7.45134698866295,
          19.083581497105016,
          -5.458359775543484,
          -4.85246927406576,
          6.589598100544898,
          2.7375656893150144,
          -3.628378501572592,
          -12.62889401027621,
          16.65919634751758,
          -0.5196165177523531,
          0.6007384838476091,
          -0.9794132116463721,
          4.645946116439932,
          -5.501539567578486,
          2.896578084439014,
          2.0480518256283364,
          -0.5099306853719742,
          3.050708561815194,
          0.1095953503073068,
          5.076155053124077,
          5.752237314616441,
          -0.3322198339447144,
          -2.2121442381102643,
          5.280163971691083,
          5.305376505747566,
          -6.277470935495338,
          -4.136586436728764,
          12.982367835705775,
          4.8800110806639845,
          -4.091676734172368,
          3.5995219226080377,
          -12.004617986755228,
          7.339732792273947,
          3.4270795530016924,
          7.03516974173486,
          2.4101932714129837,
          28.369601909646217,
          2.912193972335298,
          6.485993599012468,
          7.434100698475177,
          0.962166921458601,
          5.713747893071467,
          5.97855209601681,
          11.401206254922865,
          -4.157572947551765,
          11.01173205355515,
          5.713747893071467,
          4.509566251339518,
          3.9224338566690706,
          -0.7333513872787967,
          -0.42779672556927684,
          0.2170569304559701,
          0.2110118458934463,
          -1.3170742731031393,
          -10.233187199028288,
          4.011728261188781,
          4.761399259596336,
          14.629862471201855,
          6.548599682193386,
          -1.4784433617985882,
          8.184917036944315,
          1.6528969084242873,
          -7.5516900038794965,
          7.817035392695688,
          8.081294076176835,
          -0.8428366262292939,
          1.7001062462478627,
          5.495621144061726,
          8.538616118361567,
          2.3738394396897076,
          -6.304945732614544,
          -1.2176639821653168,
          24.802009327288708,
          -4.76750915212872,
          7.817035392695688,
          5.076155053124077,
          6.319659846652173,
          -3.870013741371968,
          4.2702435743810545,
          11.0739047645887,
          0.7975598496160792,
          3.050708561815194,
          5.187029952140859,
          -1.651111819064609,
          -8.056300875102492,
          8.253676598808438,
          12.692465469723533,
          -11.089407262741167,
          11.849280285613357,
          0.2994346082366298,
          -2.7516138178320357,
          10.284476056671432,
          14.190242626837797,
          -1.062014580820428,
          10.284476056671432,
          -2.487545187421167,
          0.09268180870967307,
          0.0018710304005436031,
          -4.801656658291961,
          -1.399517492805053,
          6.236911925224454,
          -7.233081642069417,
          2.392790419925217,
          4.093049922630166,
          10.392933196221678,
          -2.089031356491731,
          -0.31687495817604994,
          2.7375656893150144,
          -3.502858909158891,
          15.249615470024366,
          -6.135757422829637,
          36.48492157060086,
          2.440941055532264,
          9.01730251472995,
          9.82681559008721,
          -8.969506621502493,
          5.683831040680411,
          9.206625408703092,
          0.9867718833168369,
          -8.216661697173668,
          0.6007384838476091,
          -10.143314290889254,
          15.148815235675217,
          18.041013250249392,
          -5.5183378205673765,
          7.023180190941058,
          13.258841097790096,
          3.2108978628319336,
          -4.196915971903983,
          7.262983561968104,
          -0.9294189264677235,
          -5.556528404229917,
          17.714632831369826,
          0.8406389849330254,
          4.806107280375048,
          8.356591590398253,
          3.8326502595959817,
          6.548599682193386,
          2.60516873716161,
          9.113108663250099,
          13.080273644615183,
          -5.578359540521035,
          7.695880666066556,
          -7.358892882156879,
          19.86270747051501,
          -0.18749290602405663,
          -0.08897274081158164,
          -2.2121442381102643
         ],
         "yaxis": "y"
        }
       ],
       "layout": {
        "height": 250,
        "legend": {
         "tracegroupgap": 0
        },
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "rgb(36,36,36)"
            },
            "error_y": {
             "color": "rgb(36,36,36)"
            },
            "marker": {
             "line": {
              "color": "white",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "white",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "rgb(36,36,36)",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "rgb(36,36,36)"
            },
            "baxis": {
             "endlinecolor": "rgb(36,36,36)",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "rgb(36,36,36)"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "line": {
              "color": "white",
              "width": 0.6
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "parcoords"
           }
          ],
          "pie": [
           {
            "automargin": true,
            "type": "pie"
           }
          ],
          "scatter": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "rgb(237,237,237)"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "rgb(217,217,217)"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "autosize": true,
          "autotypenumbers": "strict",
          "coloraxis": {
           "colorbar": {
            "outlinewidth": 1,
            "tickcolor": "rgb(36,36,36)",
            "ticks": "outside"
           }
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "rgb(103,0,31)"
            ],
            [
             0.1,
             "rgb(178,24,43)"
            ],
            [
             0.2,
             "rgb(214,96,77)"
            ],
            [
             0.3,
             "rgb(244,165,130)"
            ],
            [
             0.4,
             "rgb(253,219,199)"
            ],
            [
             0.5,
             "rgb(247,247,247)"
            ],
            [
             0.6,
             "rgb(209,229,240)"
            ],
            [
             0.7,
             "rgb(146,197,222)"
            ],
            [
             0.8,
             "rgb(67,147,195)"
            ],
            [
             0.9,
             "rgb(33,102,172)"
            ],
            [
             1,
             "rgb(5,48,97)"
            ]
           ],
           "sequential": [
            [
             0,
             "#440154"
            ],
            [
             0.1111111111111111,
             "#482878"
            ],
            [
             0.2222222222222222,
             "#3e4989"
            ],
            [
             0.3333333333333333,
             "#31688e"
            ],
            [
             0.4444444444444444,
             "#26828e"
            ],
            [
             0.5555555555555556,
             "#1f9e89"
            ],
            [
             0.6666666666666666,
             "#35b779"
            ],
            [
             0.7777777777777778,
             "#6ece58"
            ],
            [
             0.8888888888888888,
             "#b5de2b"
            ],
            [
             1,
             "#fde725"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#440154"
            ],
            [
             0.1111111111111111,
             "#482878"
            ],
            [
             0.2222222222222222,
             "#3e4989"
            ],
            [
             0.3333333333333333,
             "#31688e"
            ],
            [
             0.4444444444444444,
             "#26828e"
            ],
            [
             0.5555555555555556,
             "#1f9e89"
            ],
            [
             0.6666666666666666,
             "#35b779"
            ],
            [
             0.7777777777777778,
             "#6ece58"
            ],
            [
             0.8888888888888888,
             "#b5de2b"
            ],
            [
             1,
             "#fde725"
            ]
           ]
          },
          "colorway": [
           "#1F77B4",
           "#FF7F0E",
           "#2CA02C",
           "#D62728",
           "#9467BD",
           "#8C564B",
           "#E377C2",
           "#7F7F7F",
           "#BCBD22",
           "#17BECF"
          ],
          "font": {
           "color": "rgb(36,36,36)"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "white",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "height": 250,
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "margin": {
           "b": 10,
           "l": 10,
           "r": 10,
           "t": 10
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "white",
          "polar": {
           "angularaxis": {
            "gridcolor": "rgb(232,232,232)",
            "linecolor": "rgb(36,36,36)",
            "showgrid": false,
            "showline": true,
            "ticks": "outside"
           },
           "bgcolor": "white",
           "radialaxis": {
            "gridcolor": "rgb(232,232,232)",
            "linecolor": "rgb(36,36,36)",
            "showgrid": false,
            "showline": true,
            "ticks": "outside"
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "white",
            "gridcolor": "rgb(232,232,232)",
            "gridwidth": 2,
            "linecolor": "rgb(36,36,36)",
            "showbackground": true,
            "showgrid": false,
            "showline": true,
            "ticks": "outside",
            "zeroline": false,
            "zerolinecolor": "rgb(36,36,36)"
           },
           "yaxis": {
            "backgroundcolor": "white",
            "gridcolor": "rgb(232,232,232)",
            "gridwidth": 2,
            "linecolor": "rgb(36,36,36)",
            "showbackground": true,
            "showgrid": false,
            "showline": true,
            "ticks": "outside",
            "zeroline": false,
            "zerolinecolor": "rgb(36,36,36)"
           },
           "zaxis": {
            "backgroundcolor": "white",
            "gridcolor": "rgb(232,232,232)",
            "gridwidth": 2,
            "linecolor": "rgb(36,36,36)",
            "showbackground": true,
            "showgrid": false,
            "showline": true,
            "ticks": "outside",
            "zeroline": false,
            "zerolinecolor": "rgb(36,36,36)"
           }
          },
          "shapedefaults": {
           "fillcolor": "black",
           "line": {
            "width": 0
           },
           "opacity": 0.3
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "rgb(232,232,232)",
            "linecolor": "rgb(36,36,36)",
            "showgrid": false,
            "showline": true,
            "ticks": "outside"
           },
           "baxis": {
            "gridcolor": "rgb(232,232,232)",
            "linecolor": "rgb(36,36,36)",
            "showgrid": false,
            "showline": true,
            "ticks": "outside"
           },
           "bgcolor": "white",
           "caxis": {
            "gridcolor": "rgb(232,232,232)",
            "linecolor": "rgb(36,36,36)",
            "showgrid": false,
            "showline": true,
            "ticks": "outside"
           }
          },
          "title": {
           "x": 0.5,
           "xanchor": "center"
          },
          "width": 350,
          "xaxis": {
           "automargin": true,
           "gridcolor": "rgb(232,232,232)",
           "linecolor": "rgb(36,36,36)",
           "showgrid": true,
           "showline": true,
           "ticks": "outside",
           "title": {
            "standoff": 15
           },
           "zeroline": false,
           "zerolinecolor": "rgb(36,36,36)"
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "rgb(232,232,232)",
           "linecolor": "rgb(36,36,36)",
           "showgrid": true,
           "showline": true,
           "ticks": "outside",
           "title": {
            "standoff": 15
           },
           "zeroline": false,
           "zerolinecolor": "rgb(36,36,36)"
          }
         }
        },
        "width": 350,
        "xaxis": {
         "anchor": "y",
         "autorange": true,
         "domain": [
          0,
          1
         ],
         "range": [
          55.866482592062745,
          215.22573458637967
         ],
         "title": {
          "text": "Predicted weight (kg)"
         },
         "type": "linear"
        },
        "yaxis": {
         "anchor": "x",
         "autorange": true,
         "domain": [
          0,
          1
         ],
         "range": [
          -24.509631553907344,
          41.16819866887298
         ],
         "title": {
          "text": "Percent error"
         },
         "type": "linear"
        }
       }
      },
      "image/png": "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",
      "image/svg+xml": [
       "<svg class=\"main-svg\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"350\" height=\"250\" style=\"\" viewBox=\"0 0 350 250\"><rect x=\"0\" y=\"0\" width=\"350\" height=\"250\" style=\"fill: rgb(255, 255, 255); fill-opacity: 1;\"/><defs id=\"defs-563cd1\"><g class=\"clips\"><clipPath id=\"clip563cd1xyplot\" class=\"plotclip\"><rect width=\"276\" height=\"175\"/></clipPath><clipPath class=\"axesclip\" id=\"clip563cd1x\"><rect x=\"64\" y=\"0\" width=\"276\" height=\"250\"/></clipPath><clipPath class=\"axesclip\" id=\"clip563cd1y\"><rect x=\"0\" y=\"16\" width=\"350\" height=\"175\"/></clipPath><clipPath class=\"axesclip\" id=\"clip563cd1xy\"><rect x=\"64\" y=\"16\" width=\"276\" height=\"175\"/></clipPath></g><g class=\"gradients\"/><g class=\"patterns\"/></defs><g class=\"bglayer\"/><g class=\"layer-below\"><g class=\"imagelayer\"/><g class=\"shapelayer\"/></g><g class=\"cartesianlayer\"><g class=\"subplot xy\"><g class=\"layer-subplot\"><g class=\"shapelayer\"/><g class=\"imagelayer\"/></g><g class=\"gridlayer\"><g class=\"x\"><path class=\"xgrid crisp\" transform=\"translate(140.44,0)\" d=\"M0,16v175\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"xgrid crisp\" transform=\"translate(227.03,0)\" d=\"M0,16v175\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"xgrid crisp\" transform=\"translate(313.63,0)\" d=\"M0,16v175\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/></g><g class=\"y\"><path class=\"ygrid crisp\" transform=\"translate(0,178.96)\" d=\"M64,0h276\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"ygrid crisp\" transform=\"translate(0,125.69)\" d=\"M64,0h276\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"ygrid crisp\" transform=\"translate(0,72.41)\" d=\"M64,0h276\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"ygrid crisp\" transform=\"translate(0,19.14)\" d=\"M64,0h276\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/></g></g><g class=\"zerolinelayer\"/><path class=\"xlines-below\"/><path class=\"ylines-below\"/><g class=\"overlines-below\"/><g class=\"xaxislayer-below\"/><g class=\"yaxislayer-below\"/><g class=\"overaxes-below\"/><g class=\"plot\" transform=\"translate(64,16)\" clip-path=\"url(#clip563cd1xyplot)\"><g class=\"scatterlayer mlayer\"><g class=\"trace scatter trace916af4\" style=\"stroke-miterlimit: 2; opacity: 1;\"><g class=\"fills\"/><g class=\"errorbars\"/><g class=\"lines\"/><g class=\"points\"><path class=\"point\" transform=\"translate(159.9,79.47)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(165.38,108.55)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(198.23,105.49)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(132.53,88.33)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(198.23,105.49)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(192.75,100.38)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,109.74)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(209.17,86.53)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(105.15,101.87)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(105.15,117.86)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(105.15,129.29)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(143.47,95.68)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(110.62,162.5)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(148.95,131.97)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(187.28,95.06)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,97.45)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,90.26)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(138,106.83)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(176.32,85.49)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(148.95,126.34)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,120.82)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.85,136.43)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.85,72.64)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(187.28,98.31)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.85,101.95)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(33.97,114.92)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.8,99.48)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(198.23,108.62)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(105.15,158.99)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(138,77.35)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.85,65.75)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.85,105.4)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(165.38,99.75)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(176.32,95.62)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.8,137.57)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(176.32,77.04)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(209.17,112.16)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(138,114.69)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(143.47,107.2)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.85,129.54)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(176.32,107.45)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,93.85)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(127.05,118.39)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(132.53,110.46)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,88.46)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(176.32,85.49)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.85,64.02)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(209.17,104.62)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(225.6,71.23)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,148.31)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,115.25)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(176.32,88.86)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(198.23,89.85)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(99.67,141.2)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(198.23,83.6)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(198.23,113.31)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.8,111.07)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(209.17,127.24)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(138,106.83)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(203.7,119.64)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(148.95,94.42)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(132.53,106.44)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(192.75,84.44)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,109.74)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(72.3,75.88)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(176.32,112.52)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,99.25)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,113.63)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(198.23,116.44)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,128.01)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(203.7,128.85)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,74.08)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(110.62,104.66)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(187.28,134.05)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(148.95,75.64)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(209.17,89.54)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(220.12,96.53)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(192.75,105.16)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(148.95,135.73)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,90.26)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(192.75,97.19)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,100.56)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(148.95,120.71)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(148.95,56.87)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(17.55,65.29)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(105.15,113.29)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(138,100.93)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(72.3,97.71)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(148.95,131.97)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(192.75,95.6)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.8,109.42)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(187.28,85.32)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.8,79.6)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(192.75,76.47)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(132.53,110.46)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(198.23,78.91)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.8,76.29)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(138,126.48)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,92.06)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.8,109.42)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(72.3,119.54)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.8,82.92)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(77.77,127.59)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(198.23,89.85)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(143.47,107.2)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(99.67,105.97)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(192.75,111.53)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.8,102.79)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,92.06)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(165.38,85.67)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(203.7,85.86)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.85,115.74)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,89.54)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(203.7,111.96)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.8,106.1)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(198.23,125.83)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(225.6,69.79)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(143.47,88)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(198.23,99.24)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(247.5,102.68)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(214.65,104.95)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(209.17,106.13)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(187.28,88.57)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(143.47,97.6)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,102.84)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(203.7,141.13)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(127.05,124.58)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(143.47,116.81)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(148.95,94.42)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(187.28,86.94)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(187.28,121.05)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,92.06)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,99.25)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(203.7,108.89)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(132.53,122.53)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,139.13)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(143.47,95.68)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.85,77.82)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.85,88.16)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(132.53,98.39)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(231.08,74.91)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(44.92,83)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,104.23)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,102.84)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(127.05,99.84)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(132.53,96.38)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,82.19)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(143.47,122.57)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(242.03,113.24)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(17.55,113.72)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(198.23,103.93)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(94.2,119.97)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(138,116.66)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,104.64)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(203.7,62.83)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(165.38,82.15)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,113.42)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(176.32,70.28)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(99.67,108.32)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.85,98.5)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(55.88,107.05)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.8,94.51)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(132.53,78.27)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(99.67,105.97)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,88.46)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(138,122.55)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(143.47,101.44)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(116.1,120.31)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(94.2,129.63)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(176.32,95.62)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(148.95,105.69)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,91.37)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(132.53,84.3)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(187.28,85.32)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,101.04)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.85,114.02)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.85,124.36)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(176.32,95.62)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(44.92,96.03)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(187.28,85.32)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(225.6,122.75)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.85,76.09)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(83.25,106.96)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.8,102.79)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(116.1,128.98)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(192.75,113.13)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(192.75,111.53)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(121.57,149.97)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(83.25,124.9)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(165.38,138.47)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(121.57,130.95)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,84.87)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(148.95,145.12)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.85,100.23)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(258.45,77.34)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.8,107.76)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(143.47,99.52)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(138,93.07)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(105.15,108.73)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.85,81.26)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.8,104.45)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(44.92,83)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(44.92,96.03)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(148.95,92.54)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(192.75,105.16)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.85,105.4)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(50.4,81.37)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,131.6)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,58.31)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(231.08,146.68)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,117.09)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(192.75,127.47)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(165.38,120.87)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(165.38,108.55)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(138,83.25)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(187.28,103.19)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(143.47,99.52)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(138,81.28)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(88.73,45.25)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(214.65,137.54)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(132.53,120.52)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(209.17,75.97)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,139.13)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(198.23,99.24)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(176.32,73.66)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(148.95,86.91)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(176.32,97.31)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(187.28,98.31)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.8,94.51)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(176.32,112.52)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(203.7,102.75)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(72.3,32.22)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(209.17,100.1)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(165.38,143.75)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,109.74)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(198.23,110.19)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(165.38,87.43)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(214.65,134.58)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,92.06)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(198.23,88.29)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(132.53,64.18)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.8,132.6)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(138,102.9)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.8,124.32)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(165.38,117.35)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(138,97)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(143.47,103.36)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(176.32,97.31)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,91.37)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,88.46)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(132.53,106.44)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(148.95,103.81)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,97.45)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(209.17,71.45)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(192.75,74.88)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,70.48)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,126.27)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.8,81.26)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(203.7,93.53)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.85,103.68)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(231.08,132.61)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,119.02)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(99.67,89.53)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(143.47,122.57)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.8,117.7)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(116.1,122.48)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(187.28,93.44)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,85.86)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(148.95,100.05)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(220.12,112.55)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.85,108.85)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,99.25)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(176.32,109.14)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.85,127.81)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(214.65,116.8)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,102.84)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(138,104.86)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(165.38,90.95)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(116.1,148.49)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(165.38,131.43)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(187.28,119.43)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(132.53,114.49)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(148.95,105.69)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,131.78)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,115.42)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.85,129.54)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.85,58.85)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(209.17,124.23)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,122.61)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(116.1,92.13)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,102.4)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.8,119.35)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.85,143.33)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(105.15,65.31)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.8,111.07)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(127.05,108.09)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.85,112.3)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(176.32,97.31)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(176.32,124.34)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(192.75,101.97)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,104.23)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(143.47,111.05)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(187.28,101.56)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(214.65,109.4)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.8,96.17)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(132.53,94.36)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.85,110.57)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(105.15,115.58)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(176.32,95.62)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(225.6,95.55)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(143.47,126.41)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(148.95,120.71)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(127.05,75.11)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(187.28,96.69)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(138,120.59)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(209.17,100.1)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(220.12,141.66)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(214.65,90.14)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,100.56)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(165.38,90.95)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(165.38,103.27)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(138,34.12)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(148.95,101.93)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(192.75,92.41)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.85,89.88)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.85,107.12)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(165.38,94.47)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(143.47,93.76)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(138,79.32)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,120.76)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,80.35)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(165.38,94.47)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(198.23,97.67)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(198.23,99.24)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(116.1,111.64)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(176.32,110.83)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(110.62,109.11)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(143.47,109.13)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(148.95,113.2)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(127.05,136.95)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(176.32,99)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(138,97)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(143.47,70.72)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(176.32,92.24)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,113.63)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.8,87.88)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(143.47,105.28)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,129.8)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(176.32,88.86)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.85,88.16)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(121.57,111.93)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(192.75,105.16)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,95.05)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(187.28,86.94)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(143.47,103.36)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(138,126.48)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(187.28,112.93)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,43.62)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(94.2,122.39)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(176.32,88.86)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.8,96.17)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.8,92.85)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(236.55,120)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(187.28,98.31)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(110.62,80.19)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(148.95,107.56)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(187.28,101.56)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(77.77,95.87)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(72.3,114.09)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(116.1,131.15)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,87.7)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,75.88)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.8,139.23)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(121.57,78.12)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(203.7,108.89)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(77.77,117.02)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(132.53,82.29)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(148.95,71.89)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(176.32,112.52)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(132.53,82.29)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(192.75,116.31)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(148.95,109.44)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(187.28,109.68)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(116.1,122.48)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,113.42)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(138,93.07)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(198.23,128.95)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(258.45,103.31)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(192.75,98.78)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(209.17,82)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,115.25)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(61.35,110.53)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,102.4)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.9,119.02)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(110.62,69.07)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(176.32,126.03)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(138,12.5)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(187.28,103.19)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(165.38,85.67)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(209.17,83.51)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(110.62,133.58)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(198.23,94.55)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(198.23,85.16)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(198.23,107.06)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(105.15,131.57)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(127.05,108.09)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(165.38,136.71)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,69.33)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(138,61.63)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(165.38,124.39)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(94.2,90.98)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.85,74.37)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.8,101.13)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(165.38,120.87)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(132.53,90.34)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(209.17,112.16)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(143.47,124.49)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(148.95,62.5)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(176.32,107.45)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,96.88)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(165.38,87.43)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.8,99.48)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(176.32,92.24)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(203.7,102.75)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(127.05,85.41)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.42,74.84)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(132.53,124.55)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(165.38,89.19)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.8,129.29)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(72.3,56.78)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(198.23,110.19)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(88.73,109.92)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(105.15,115.58)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/></g><g class=\"text\"/></g></g></g><g class=\"overplot\"/><path class=\"xlines-above crisp\" d=\"M63,191.5H340\" style=\"fill: none; stroke-width: 1px; stroke: rgb(36, 36, 36); stroke-opacity: 1;\"/><path class=\"ylines-above crisp\" d=\"M63.5,16V191\" style=\"fill: none; stroke-width: 1px; stroke: rgb(36, 36, 36); stroke-opacity: 1;\"/><g class=\"overlines-above\"/><g class=\"xaxislayer-above\"><path class=\"xtick ticks crisp\" d=\"M0,192v5\" transform=\"translate(140.44,0)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"xtick ticks crisp\" d=\"M0,192v5\" transform=\"translate(227.03,0)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"xtick ticks crisp\" d=\"M0,192v5\" transform=\"translate(313.63,0)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><g class=\"xtick\"><text text-anchor=\"middle\" x=\"0\" y=\"211.4\" transform=\"translate(140.44,0)\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\">100</text></g><g class=\"xtick\"><text text-anchor=\"middle\" x=\"0\" y=\"211.4\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(227.03,0)\">150</text></g><g class=\"xtick\"><text text-anchor=\"middle\" x=\"0\" y=\"211.4\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(313.63,0)\">200</text></g></g><g class=\"yaxislayer-above\"><path class=\"ytick ticks crisp\" d=\"M63,0h-5\" transform=\"translate(0,178.96)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"ytick ticks crisp\" d=\"M63,0h-5\" transform=\"translate(0,125.69)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"ytick ticks crisp\" d=\"M63,0h-5\" transform=\"translate(0,72.41)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"ytick ticks crisp\" d=\"M63,0h-5\" transform=\"translate(0,19.14)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><g class=\"ytick\"><text text-anchor=\"end\" x=\"55.6\" y=\"4.199999999999999\" transform=\"translate(0,178.96)\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\">−20</text></g><g class=\"ytick\"><text text-anchor=\"end\" x=\"55.6\" y=\"4.199999999999999\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(0,125.69)\">0</text></g><g class=\"ytick\"><text text-anchor=\"end\" x=\"55.6\" y=\"4.199999999999999\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(0,72.41)\">20</text></g><g class=\"ytick\"><text text-anchor=\"end\" x=\"55.6\" y=\"4.199999999999999\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(0,19.14)\">40</text></g></g><g class=\"overaxes-above\"/></g></g><g class=\"polarlayer\"/><g class=\"smithlayer\"/><g class=\"ternarylayer\"/><g class=\"geolayer\"/><g class=\"funnelarealayer\"/><g class=\"pielayer\"/><g class=\"iciclelayer\"/><g class=\"treemaplayer\"/><g class=\"sunburstlayer\"/><g class=\"glimages\"/><defs id=\"topdefs-563cd1\"><g class=\"clips\"/></defs><g class=\"layer-above\"><g class=\"imagelayer\"/><g class=\"shapelayer\"/></g><g class=\"infolayer\"><g class=\"g-gtitle\"/><g class=\"g-xtitle\"><text class=\"xtitle\" x=\"202\" y=\"239.70625\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(36, 36, 36); opacity: 1; font-weight: normal; white-space: pre;\">Predicted weight (kg)</text></g><g class=\"g-ytitle\" transform=\"translate(4.7841796875,0)\"><text class=\"ytitle\" transform=\"rotate(-90,10.215625000000003,103.5)\" x=\"10.215625000000003\" y=\"103.5\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(36, 36, 36); opacity: 1; font-weight: normal; white-space: pre;\">Percent error</text></g></g></svg>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "resid = pd.DataFrame({'Predicted weight (kg)': predicted, 'Percent error': resids})\n",
    "px.scatter(resid, x='Predicted weight (kg)', y='Percent error',\n",
    "           width=350, height=250)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With the simplest model, some of the predictions are off by 20% to 30%. Let's see if a slightly more complicated model improves the predictions. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fitting a Multiple Linear Model \n",
    "\n",
    "Let's consider additional models that incorporate the other numeric variables.\n",
    "We have three numeric variables that measure the donkey's girth, length, and\n",
    "height, and there are seven total ways to combine these variables in a model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['Girth'],\n",
       " ['Length'],\n",
       " ['Height'],\n",
       " ['Girth', 'Length'],\n",
       " ['Girth', 'Height'],\n",
       " ['Length', 'Height'],\n",
       " ['Girth', 'Length', 'Height']]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import itertools\n",
    "\n",
    "numeric_vars = ['Girth', 'Length', 'Height']\n",
    "\n",
    "models = [list(subset)\n",
    "          for n in [1, 2, 3]\n",
    "          for subset in itertools.combinations(numeric_vars, n)]\n",
    "models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For each of these variable combinations, we can fit a model with our special loss function.\n",
    "Then we can look at how well each model does on the train set:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def training_error(model):\n",
    "    X = train_set.assign(intr=1)[['intr', *model]]\n",
    "    theta_hat = minimize(training_loss(X, y), np.ones(X.shape[1]))['x']\n",
    "    predicted = X @ theta_hat\n",
    "    return np.mean(anes_loss(100 * (y - predicted)/ predicted))\n",
    "\n",
    "model_risks = [\n",
    "    training_error(model)\n",
    "    for model in models\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "tags": [
     "remove-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>model</th>\n",
       "      <th>mean_training_error</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>[Girth]</td>\n",
       "      <td>94.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>[Length]</td>\n",
       "      <td>200.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>[Height]</td>\n",
       "      <td>268.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>[Girth, Length]</td>\n",
       "      <td>65.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>[Girth, Height]</td>\n",
       "      <td>86.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>[Length, Height]</td>\n",
       "      <td>151.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>[Girth, Length, Height]</td>\n",
       "      <td>63.44</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     model  mean_training_error\n",
       "0                  [Girth]                94.36\n",
       "1                 [Length]               200.55\n",
       "2                 [Height]               268.88\n",
       "3          [Girth, Length]                65.65\n",
       "4          [Girth, Height]                86.18\n",
       "5         [Length, Height]               151.15\n",
       "6  [Girth, Length, Height]                63.44"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame({'model': models, 'mean_training_error': model_risks})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we stated earlier, the girth of the donkey is the single best predictor for weight. However, the combination of  girth and length has an average loss that is quite a bit smaller than girth alone, and this particular two-variable model is nearly as good as the model that includes all three. Since we want a simple model, we select the two-variable model over the three-variable one.\n",
    "\n",
    "Next, we use feature engineering to incorporate categorical variables into the model, which improves our model."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Bringing Qualitative Features into the Model\n",
    "\n",
    "In our exploratory analysis, we found that the box plots of weight for donkey's body condition and age could contain useful information in predicting weight. \n",
    "Since these are categorical features, we can transform them to 0-1 variables with one-hot encoding, as explained in {numref}`Chapter %s <ch:linear>`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "One-hot encoding lets us adjust the intercept term in the model for each combination of categories. Our current model includes the numeric variables girth and length: \n",
    "\n",
    "$$\n",
    "\\theta_0 + \\theta_1 \\text{Girth} + \\theta_2 \\text{Length}\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If we cleaned up the age feature to consist of three categories---`Age<2`, `Age2-5`, and `Age>5`---a one-hot encoding of age creates three 0-1 features, one for each category. Including the one-hot encoded feature in the model gives:\n",
    "\n",
    "$$\n",
    "\\begin{aligned}\n",
    "    \\theta_0\n",
    "    & + \\theta_1  \\text{Girth }\n",
    "      + \\theta_2  \\text{Length } \\\\\n",
    "    & + \\theta_3  \\text{Age<2 }\n",
    "      + \\theta_4  \\text{Age2-5 }\n",
    "\\end{aligned}\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this model, \n",
    "`Age<2` is 1 for a donkey younger than 2 and 0 otherwise.\n",
    "Similarly, `Age2-5` is 1 for a donkey between 2 and 5 years old and 0 otherwise.\n",
    "\n",
    "We can think of this model as fitting three linear models that are \n",
    "identical except for the size of the constant, since the model\n",
    "is equivalent to:\n",
    "\n",
    "$$\n",
    "\\begin{aligned}\n",
    "(\\theta_0 + \\theta_3 ) + \\theta_1 \\text{Girth} + \\theta_2 \\text{Length}\n",
    "  & ~~~~~~~~~~\\text{for a donkey under 2}\\\\\n",
    "(\\theta_0 + \\theta_4 ) + \\theta_1 \\text{Girth} + \\theta_2 \\text{Length}\n",
    "  & ~~~~~~~~~~\\text{for a donkey between 2 and 4}\\\\\n",
    "\\theta_0  + \\theta_1 \\text{Girth} + \\theta_2 \\text{Length}\n",
    "  & ~~~~~~~~~~\\text{for a donkey over 5}\n",
    "\\end{aligned}\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's apply a one-hot encoding to all three of our categorical variables\n",
    "(body condition, age, and  sex):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>intr</th>\n",
       "      <th>Length</th>\n",
       "      <th>Girth</th>\n",
       "      <th>BCS_1.5</th>\n",
       "      <th>...</th>\n",
       "      <th>Age_&lt;2</th>\n",
       "      <th>Age_&gt;20</th>\n",
       "      <th>Sex_gelding</th>\n",
       "      <th>Sex_stallion</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>230</th>\n",
       "      <td>1</td>\n",
       "      <td>101</td>\n",
       "      <td>116</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>1</td>\n",
       "      <td>92</td>\n",
       "      <td>117</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>354</th>\n",
       "      <td>1</td>\n",
       "      <td>103</td>\n",
       "      <td>123</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>1</td>\n",
       "      <td>93</td>\n",
       "      <td>123</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>1</td>\n",
       "      <td>89</td>\n",
       "      <td>103</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>381</th>\n",
       "      <td>1</td>\n",
       "      <td>86</td>\n",
       "      <td>106</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>433 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     intr  Length  Girth  BCS_1.5  ...  Age_<2  Age_>20  Sex_gelding  \\\n",
       "230     1     101    116        0  ...       0        0            0   \n",
       "74      1      92    117        0  ...       0        0            0   \n",
       "354     1     103    123        0  ...       0        1            0   \n",
       "..    ...     ...    ...      ...  ...     ...      ...          ...   \n",
       "157     1      93    123        0  ...       0        0            0   \n",
       "41      1      89    103        0  ...       1        0            0   \n",
       "381     1      86    106        0  ...       0        0            0   \n",
       "\n",
       "     Sex_stallion  \n",
       "230             1  \n",
       "74              1  \n",
       "354             0  \n",
       "..            ...  \n",
       "157             1  \n",
       "41              0  \n",
       "381             0  \n",
       "\n",
       "[433 rows x 15 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_one_hot = (\n",
    "    train_set.assign(intr=1)\n",
    "    [['intr', 'Length', 'Girth', 'BCS', 'Age', 'Sex']]\n",
    "    .pipe(pd.get_dummies, columns=['BCS', 'Age', 'Sex'])\n",
    "    .drop(columns=['BCS_3.0', 'Age_5-10', 'Sex_female'])\n",
    ")\n",
    "X_one_hot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We dropped one dummy variable for each categorical feature.\n",
    "Since `BCS`, `Age`, and `Sex` have six, six, and three categories, respectively,\n",
    "we have added 12 dummy variables to the design matrix for a total of 15 columns,\n",
    "including the intercept term, girth and length. \n",
    "\n",
    "Let's see which categorical variables, if any, improve on our two-variable model. To do this, we can fit the model that includes the dummies from all three categorical features, along with girth and length:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training error: 51.47\n"
     ]
    }
   ],
   "source": [
    "results = minimize(training_loss(X_one_hot, y), np.ones(X_one_hot.shape[1]))\n",
    "\n",
    "theta_hat = results['x']\n",
    "\n",
    "y_pred = X_one_hot @ theta_hat\n",
    "training_error = (np.mean(anes_loss(100 * (y - y_pred)/ y_pred)))\n",
    "\n",
    "print(f'Training error: {training_error:.2f}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "According to average loss, this model does better than the previous model with only `Girth` and `Length`.\n",
    "But let's try to make this model simpler while keeping its accuracy.\n",
    "To do this, we look at the coefficients for each of the dummy variables to see how close they are to 0 and to one another. In other words, we want to see how much the intercept might change if we include the coefficients in the model.\n",
    "A plot of the coefficients will make this comparison easy:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "hovertemplate": "var=%{x}<br>theta_hat=%{y}<extra></extra>",
         "legendgroup": "",
         "marker": {
          "color": "#1F77B4",
          "size": 10,
          "symbol": "circle"
         },
         "mode": "markers",
         "name": "",
         "orientation": "v",
         "showlegend": false,
         "type": "scatter",
         "x": [
          "BCS_1.5",
          "BCS_2.0",
          "BCS_2.5",
          "BCS_3.5",
          "BCS_4.0"
         ],
         "xaxis": "x",
         "y": [
          -6.837371374838559,
          -6.7541904288951695,
          -4.913100527819169,
          7.386560482722495,
          19.2459371043036
         ],
         "yaxis": "y"
        },
        {
         "hovertemplate": "var=%{x}<br>theta_hat=%{y}<extra></extra>",
         "legendgroup": "",
         "marker": {
          "color": "#1F77B4",
          "size": 10,
          "symbol": "circle"
         },
         "mode": "markers",
         "name": "",
         "orientation": "v",
         "showlegend": false,
         "type": "scatter",
         "x": [
          "Sex_gelding",
          "Sex_stallion"
         ],
         "xaxis": "x2",
         "y": [
          1.2003842619383769,
          2.797943693726871
         ],
         "yaxis": "y2"
        },
        {
         "hovertemplate": "var=%{x}<br>theta_hat=%{y}<extra></extra>",
         "legendgroup": "",
         "marker": {
          "color": "#1F77B4",
          "size": 10,
          "symbol": "circle"
         },
         "mode": "markers",
         "name": "",
         "orientation": "v",
         "showlegend": false,
         "type": "scatter",
         "x": [
          "Age_<2",
          "Age_2-5",
          "Age_10-15",
          "Age_15-20",
          "Age_>20"
         ],
         "xaxis": "x3",
         "y": [
          -4.691130506905128,
          -2.3405865751927304,
          1.5592573159218777,
          2.5595437994163444,
          1.3530591778905496
         ],
         "yaxis": "y3"
        }
       ],
       "layout": {
        "height": 250,
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "rgb(36,36,36)"
            },
            "error_y": {
             "color": "rgb(36,36,36)"
            },
            "marker": {
             "line": {
              "color": "white",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "white",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "rgb(36,36,36)",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "rgb(36,36,36)"
            },
            "baxis": {
             "endlinecolor": "rgb(36,36,36)",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "rgb(36,36,36)"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "line": {
              "color": "white",
              "width": 0.6
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "parcoords"
           }
          ],
          "pie": [
           {
            "automargin": true,
            "type": "pie"
           }
          ],
          "scatter": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "rgb(237,237,237)"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "rgb(217,217,217)"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "autosize": true,
          "autotypenumbers": "strict",
          "coloraxis": {
           "colorbar": {
            "outlinewidth": 1,
            "tickcolor": "rgb(36,36,36)",
            "ticks": "outside"
           }
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "rgb(103,0,31)"
            ],
            [
             0.1,
             "rgb(178,24,43)"
            ],
            [
             0.2,
             "rgb(214,96,77)"
            ],
            [
             0.3,
             "rgb(244,165,130)"
            ],
            [
             0.4,
             "rgb(253,219,199)"
            ],
            [
             0.5,
             "rgb(247,247,247)"
            ],
            [
             0.6,
             "rgb(209,229,240)"
            ],
            [
             0.7,
             "rgb(146,197,222)"
            ],
            [
             0.8,
             "rgb(67,147,195)"
            ],
            [
             0.9,
             "rgb(33,102,172)"
            ],
            [
             1,
             "rgb(5,48,97)"
            ]
           ],
           "sequential": [
            [
             0,
             "#440154"
            ],
            [
             0.1111111111111111,
             "#482878"
            ],
            [
             0.2222222222222222,
             "#3e4989"
            ],
            [
             0.3333333333333333,
             "#31688e"
            ],
            [
             0.4444444444444444,
             "#26828e"
            ],
            [
             0.5555555555555556,
             "#1f9e89"
            ],
            [
             0.6666666666666666,
             "#35b779"
            ],
            [
             0.7777777777777778,
             "#6ece58"
            ],
            [
             0.8888888888888888,
             "#b5de2b"
            ],
            [
             1,
             "#fde725"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#440154"
            ],
            [
             0.1111111111111111,
             "#482878"
            ],
            [
             0.2222222222222222,
             "#3e4989"
            ],
            [
             0.3333333333333333,
             "#31688e"
            ],
            [
             0.4444444444444444,
             "#26828e"
            ],
            [
             0.5555555555555556,
             "#1f9e89"
            ],
            [
             0.6666666666666666,
             "#35b779"
            ],
            [
             0.7777777777777778,
             "#6ece58"
            ],
            [
             0.8888888888888888,
             "#b5de2b"
            ],
            [
             1,
             "#fde725"
            ]
           ]
          },
          "colorway": [
           "#1F77B4",
           "#FF7F0E",
           "#2CA02C",
           "#D62728",
           "#9467BD",
           "#8C564B",
           "#E377C2",
           "#7F7F7F",
           "#BCBD22",
           "#17BECF"
          ],
          "font": {
           "color": "rgb(36,36,36)"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "white",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "height": 250,
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "margin": {
           "b": 10,
           "l": 10,
           "r": 10,
           "t": 10
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "white",
          "polar": {
           "angularaxis": {
            "gridcolor": "rgb(232,232,232)",
            "linecolor": "rgb(36,36,36)",
            "showgrid": false,
            "showline": true,
            "ticks": "outside"
           },
           "bgcolor": "white",
           "radialaxis": {
            "gridcolor": "rgb(232,232,232)",
            "linecolor": "rgb(36,36,36)",
            "showgrid": false,
            "showline": true,
            "ticks": "outside"
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "white",
            "gridcolor": "rgb(232,232,232)",
            "gridwidth": 2,
            "linecolor": "rgb(36,36,36)",
            "showbackground": true,
            "showgrid": false,
            "showline": true,
            "ticks": "outside",
            "zeroline": false,
            "zerolinecolor": "rgb(36,36,36)"
           },
           "yaxis": {
            "backgroundcolor": "white",
            "gridcolor": "rgb(232,232,232)",
            "gridwidth": 2,
            "linecolor": "rgb(36,36,36)",
            "showbackground": true,
            "showgrid": false,
            "showline": true,
            "ticks": "outside",
            "zeroline": false,
            "zerolinecolor": "rgb(36,36,36)"
           },
           "zaxis": {
            "backgroundcolor": "white",
            "gridcolor": "rgb(232,232,232)",
            "gridwidth": 2,
            "linecolor": "rgb(36,36,36)",
            "showbackground": true,
            "showgrid": false,
            "showline": true,
            "ticks": "outside",
            "zeroline": false,
            "zerolinecolor": "rgb(36,36,36)"
           }
          },
          "shapedefaults": {
           "fillcolor": "black",
           "line": {
            "width": 0
           },
           "opacity": 0.3
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "rgb(232,232,232)",
            "linecolor": "rgb(36,36,36)",
            "showgrid": false,
            "showline": true,
            "ticks": "outside"
           },
           "baxis": {
            "gridcolor": "rgb(232,232,232)",
            "linecolor": "rgb(36,36,36)",
            "showgrid": false,
            "showline": true,
            "ticks": "outside"
           },
           "bgcolor": "white",
           "caxis": {
            "gridcolor": "rgb(232,232,232)",
            "linecolor": "rgb(36,36,36)",
            "showgrid": false,
            "showline": true,
            "ticks": "outside"
           }
          },
          "title": {
           "x": 0.5,
           "xanchor": "center"
          },
          "width": 350,
          "xaxis": {
           "automargin": true,
           "gridcolor": "rgb(232,232,232)",
           "linecolor": "rgb(36,36,36)",
           "showgrid": true,
           "showline": true,
           "ticks": "outside",
           "title": {
            "standoff": 15
           },
           "zeroline": false,
           "zerolinecolor": "rgb(36,36,36)"
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "rgb(232,232,232)",
           "linecolor": "rgb(36,36,36)",
           "showgrid": true,
           "showline": true,
           "ticks": "outside",
           "title": {
            "standoff": 15
           },
           "zeroline": false,
           "zerolinecolor": "rgb(36,36,36)"
          }
         }
        },
        "width": 550,
        "xaxis": {
         "anchor": "y",
         "autorange": true,
         "domain": [
          0,
          0.30333333333333334
         ],
         "range": [
          -0.4790291465586844,
          4.479029146558684
         ],
         "tickangle": 45,
         "type": "category"
        },
        "xaxis2": {
         "anchor": "y2",
         "autorange": true,
         "domain": [
          0.37,
          0.5433333333333333
         ],
         "range": [
          -0.17857058503979778,
          1.1785705850397978
         ],
         "tickangle": 45,
         "type": "category"
        },
        "xaxis3": {
         "anchor": "y3",
         "autorange": true,
         "domain": [
          0.61,
          1
         ],
         "range": [
          -0.4169599416721583,
          4.416959941672158
         ],
         "tickangle": 45,
         "type": "category"
        },
        "yaxis": {
         "anchor": "x",
         "autorange": true,
         "domain": [
          0,
          1
         ],
         "range": [
          -9.6361764575483,
          22.04474218701334
         ],
         "title": {
          "text": "theta_hat"
         },
         "type": "linear"
        },
        "yaxis2": {
         "anchor": "x2",
         "autorange": true,
         "domain": [
          0,
          1
         ],
         "matches": "y",
         "range": [
          -9.6361764575483,
          22.04474218701334
         ],
         "showticklabels": false,
         "type": "linear"
        },
        "yaxis3": {
         "anchor": "x3",
         "autorange": true,
         "domain": [
          0,
          1
         ],
         "matches": "y",
         "range": [
          -9.6361764575483,
          22.04474218701334
         ],
         "showticklabels": false,
         "type": "linear"
        }
       }
      },
      "image/png": "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",
      "image/svg+xml": [
       "<svg class=\"main-svg\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"550\" height=\"250\" style=\"\" viewBox=\"0 0 550 250\"><rect x=\"0\" y=\"0\" width=\"550\" height=\"250\" style=\"fill: rgb(255, 255, 255); fill-opacity: 1;\"/><defs id=\"defs-bbcaff\"><g class=\"clips\"><clipPath id=\"clipbbcaffxyplot\" class=\"plotclip\"><rect width=\"134.37666666666667\" height=\"162\"/></clipPath><clipPath id=\"clipbbcaffx2y2plot\" class=\"plotclip\"><rect width=\"76.78666666666668\" height=\"162\"/></clipPath><clipPath id=\"clipbbcaffx3y3plot\" class=\"plotclip\"><rect width=\"172.77\" height=\"162\"/></clipPath><clipPath class=\"axesclip\" id=\"clipbbcaffx\"><rect x=\"57\" y=\"0\" width=\"134.37666666666667\" height=\"250\"/></clipPath><clipPath class=\"axesclip\" id=\"clipbbcaffy\"><rect x=\"0\" y=\"10\" width=\"550\" height=\"162\"/></clipPath><clipPath class=\"axesclip\" id=\"clipbbcaffxy\"><rect x=\"57\" y=\"10\" width=\"134.37666666666667\" height=\"162\"/></clipPath><clipPath class=\"axesclip\" id=\"clipbbcaffy2\"><rect x=\"0\" y=\"10\" width=\"550\" height=\"162\"/></clipPath><clipPath class=\"axesclip\" id=\"clipbbcaffxy2\"><rect x=\"57\" y=\"10\" width=\"134.37666666666667\" height=\"162\"/></clipPath><clipPath class=\"axesclip\" id=\"clipbbcaffy3\"><rect x=\"0\" y=\"10\" width=\"550\" height=\"162\"/></clipPath><clipPath class=\"axesclip\" id=\"clipbbcaffxy3\"><rect x=\"57\" y=\"10\" width=\"134.37666666666667\" height=\"162\"/></clipPath><clipPath class=\"axesclip\" id=\"clipbbcaffx2\"><rect x=\"220.91\" y=\"0\" width=\"76.78666666666668\" height=\"250\"/></clipPath><clipPath class=\"axesclip\" id=\"clipbbcaffx2y\"><rect x=\"220.91\" y=\"10\" width=\"76.78666666666668\" height=\"162\"/></clipPath><clipPath class=\"axesclip\" id=\"clipbbcaffx2y2\"><rect x=\"220.91\" y=\"10\" width=\"76.78666666666668\" height=\"162\"/></clipPath><clipPath class=\"axesclip\" id=\"clipbbcaffx2y3\"><rect x=\"220.91\" y=\"10\" width=\"76.78666666666668\" height=\"162\"/></clipPath><clipPath class=\"axesclip\" id=\"clipbbcaffx3\"><rect x=\"327.23\" y=\"0\" width=\"172.77\" height=\"250\"/></clipPath><clipPath class=\"axesclip\" id=\"clipbbcaffx3y\"><rect x=\"327.23\" y=\"10\" width=\"172.77\" height=\"162\"/></clipPath><clipPath class=\"axesclip\" id=\"clipbbcaffx3y2\"><rect x=\"327.23\" y=\"10\" width=\"172.77\" height=\"162\"/></clipPath><clipPath class=\"axesclip\" id=\"clipbbcaffx3y3\"><rect x=\"327.23\" y=\"10\" width=\"172.77\" height=\"162\"/></clipPath></g><g class=\"gradients\"/><g class=\"patterns\"/></defs><g class=\"bglayer\"/><g class=\"layer-below\"><g class=\"imagelayer\"/><g class=\"shapelayer\"/></g><g class=\"cartesianlayer\"><g class=\"subplot xy\"><g class=\"layer-subplot\"><g class=\"shapelayer\"/><g class=\"imagelayer\"/></g><g class=\"gridlayer\"><g class=\"x\"><path class=\"xgrid crisp\" transform=\"translate(69.97,0)\" d=\"M0,10v162\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"xgrid crisp\" transform=\"translate(97.08,0)\" d=\"M0,10v162\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"xgrid crisp\" transform=\"translate(124.19,0)\" d=\"M0,10v162\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"xgrid crisp\" transform=\"translate(151.3,0)\" d=\"M0,10v162\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"xgrid crisp\" transform=\"translate(178.41,0)\" d=\"M0,10v162\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/></g><g class=\"y\"><path class=\"ygrid crisp\" transform=\"translate(0,122.71)\" d=\"M57,0h134.37666666666667\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"ygrid crisp\" transform=\"translate(0,71.6)\" d=\"M57,0h134.37666666666667\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"ygrid crisp\" transform=\"translate(0,20.5)\" d=\"M57,0h134.37666666666667\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/></g></g><g class=\"zerolinelayer\"/><path class=\"xlines-below\"/><path class=\"ylines-below\"/><g class=\"overlines-below\"/><g class=\"xaxislayer-below\"/><g class=\"yaxislayer-below\"/><g class=\"overaxes-below\"/><g class=\"plot\" transform=\"translate(57,10)\" clip-path=\"url(#clipbbcaffxyplot)\"><g class=\"scatterlayer mlayer\"><g class=\"trace scatter trace0df054\" style=\"stroke-miterlimit: 2; opacity: 1;\"><g class=\"fills\"/><g class=\"errorbars\"/><g class=\"lines\"/><g class=\"points\"><path class=\"point\" transform=\"translate(12.97,147.65)\" d=\"M5,0A5,5 0 1,1 0,-5A5,5 0 0,1 5,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(40.08,147.22)\" d=\"M5,0A5,5 0 1,1 0,-5A5,5 0 0,1 5,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(67.19,137.82)\" d=\"M5,0A5,5 0 1,1 0,-5A5,5 0 0,1 5,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(94.3,74.96)\" d=\"M5,0A5,5 0 1,1 0,-5A5,5 0 0,1 5,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(121.41,14.35)\" d=\"M5,0A5,5 0 1,1 0,-5A5,5 0 0,1 5,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/></g><g class=\"text\"/></g></g></g><g class=\"overplot\"/><path class=\"xlines-above crisp\" d=\"M56,172.5H191.37666666666667\" style=\"fill: none; stroke-width: 1px; stroke: rgb(36, 36, 36); stroke-opacity: 1;\"/><path class=\"ylines-above crisp\" d=\"M56.5,10V172\" style=\"fill: none; stroke-width: 1px; stroke: rgb(36, 36, 36); stroke-opacity: 1;\"/><g class=\"overlines-above\"/><g class=\"xaxislayer-above\"><path class=\"xtick ticks crisp\" d=\"M0,173v5\" transform=\"translate(69.97,0)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"xtick ticks crisp\" d=\"M0,173v5\" transform=\"translate(97.08,0)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"xtick ticks crisp\" d=\"M0,173v5\" transform=\"translate(124.19,0)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"xtick ticks crisp\" d=\"M0,173v5\" transform=\"translate(151.3,0)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"xtick ticks crisp\" d=\"M0,173v5\" transform=\"translate(178.41,0)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><g class=\"xtick\"><text text-anchor=\"start\" x=\"0\" y=\"192.4\" transform=\"translate(69.97,0) rotate(45,0,186.4)\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\">BCS_1.5</text></g><g class=\"xtick\"><text text-anchor=\"start\" x=\"0\" y=\"192.4\" transform=\"translate(97.08,0) rotate(45,0,186.4)\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\">BCS_2.0</text></g><g class=\"xtick\"><text text-anchor=\"start\" x=\"0\" y=\"192.4\" transform=\"translate(124.19,0) rotate(45,0,186.4)\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\">BCS_2.5</text></g><g class=\"xtick\"><text text-anchor=\"start\" x=\"0\" y=\"192.4\" transform=\"translate(151.3,0) rotate(45,0,186.4)\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\">BCS_3.5</text></g><g class=\"xtick\"><text text-anchor=\"start\" x=\"0\" y=\"192.4\" transform=\"translate(178.41,0) rotate(45,0,186.4)\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\">BCS_4.0</text></g></g><g class=\"yaxislayer-above\"><path class=\"ytick ticks crisp\" d=\"M56,0h-5\" transform=\"translate(0,122.71)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"ytick ticks crisp\" d=\"M56,0h-5\" transform=\"translate(0,71.6)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"ytick ticks crisp\" d=\"M56,0h-5\" transform=\"translate(0,20.5)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><g class=\"ytick\"><text text-anchor=\"end\" x=\"48.6\" y=\"4.199999999999999\" transform=\"translate(0,122.71)\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\">0</text></g><g class=\"ytick\"><text text-anchor=\"end\" x=\"48.6\" y=\"4.199999999999999\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(0,71.6)\">10</text></g><g class=\"ytick\"><text text-anchor=\"end\" x=\"48.6\" y=\"4.199999999999999\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(0,20.5)\">20</text></g></g><g class=\"overaxes-above\"/></g><g class=\"subplot x2y2\"><g class=\"layer-subplot\"><g class=\"shapelayer\"/><g class=\"imagelayer\"/></g><g class=\"gridlayer\"><g class=\"x2\"><path class=\"x2grid crisp\" transform=\"translate(231,0)\" d=\"M0,10v162\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"x2grid crisp\" transform=\"translate(287.61,0)\" d=\"M0,10v162\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/></g><g class=\"y2\"><path class=\"y2grid crisp\" transform=\"translate(0,122.71)\" d=\"M220.91,0h76.78666666666668\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"y2grid crisp\" transform=\"translate(0,71.6)\" d=\"M220.91,0h76.78666666666668\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"y2grid crisp\" transform=\"translate(0,20.5)\" d=\"M220.91,0h76.78666666666668\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/></g></g><g class=\"zerolinelayer\"/><path class=\"xlines-below\"/><path class=\"ylines-below\"/><g class=\"overlines-below\"/><g class=\"xaxislayer-below\"/><g class=\"yaxislayer-below\"/><g class=\"overaxes-below\"/><g class=\"plot\" transform=\"translate(220.91,10)\" clip-path=\"url(#clipbbcaffx2y2plot)\"><g class=\"scatterlayer mlayer\"><g class=\"trace scatter trace9710e0\" style=\"stroke-miterlimit: 2; opacity: 1;\"><g class=\"fills\"/><g class=\"errorbars\"/><g class=\"lines\"/><g class=\"points\"><path class=\"point\" transform=\"translate(10.09,106.57)\" d=\"M5,0A5,5 0 1,1 0,-5A5,5 0 0,1 5,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(66.7,98.41)\" d=\"M5,0A5,5 0 1,1 0,-5A5,5 0 0,1 5,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/></g><g class=\"text\"/></g></g></g><g class=\"overplot\"/><path class=\"xlines-above crisp\" d=\"M219.91,172.5H297.69666666666666\" style=\"fill: none; stroke-width: 1px; stroke: rgb(36, 36, 36); stroke-opacity: 1;\"/><path class=\"ylines-above crisp\" d=\"M220.41,10V172\" style=\"fill: none; stroke-width: 1px; stroke: rgb(36, 36, 36); stroke-opacity: 1;\"/><g class=\"overlines-above\"/><g class=\"xaxislayer-above\"><path class=\"x2tick ticks crisp\" d=\"M0,173v5\" transform=\"translate(231,0)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"x2tick ticks crisp\" d=\"M0,173v5\" transform=\"translate(287.61,0)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><g class=\"x2tick\"><text text-anchor=\"start\" x=\"0\" y=\"192.4\" transform=\"translate(231,0) rotate(45,0,186.4)\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\">Sex_gelding</text></g><g class=\"x2tick\"><text text-anchor=\"start\" x=\"0\" y=\"192.4\" transform=\"translate(287.61,0) rotate(45,0,186.4)\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\">Sex_stallion</text></g></g><g class=\"yaxislayer-above\"><path class=\"y2tick ticks crisp\" d=\"M219.91,0h-5\" transform=\"translate(0,122.71)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"y2tick ticks crisp\" d=\"M219.91,0h-5\" transform=\"translate(0,71.6)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"y2tick ticks crisp\" d=\"M219.91,0h-5\" transform=\"translate(0,20.5)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/></g><g class=\"overaxes-above\"/></g><g class=\"subplot x3y3\"><g class=\"layer-subplot\"><g class=\"shapelayer\"/><g class=\"imagelayer\"/></g><g class=\"gridlayer\"><g class=\"x3\"><path class=\"x3grid crisp\" transform=\"translate(342.12,0)\" d=\"M0,10v162\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"x3grid crisp\" transform=\"translate(377.87,0)\" d=\"M0,10v162\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"x3grid crisp\" transform=\"translate(413.62,0)\" d=\"M0,10v162\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"x3grid crisp\" transform=\"translate(449.36,0)\" d=\"M0,10v162\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"x3grid crisp\" transform=\"translate(485.11,0)\" d=\"M0,10v162\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/></g><g class=\"y3\"><path class=\"y3grid crisp\" transform=\"translate(0,122.71)\" d=\"M327.23,0h172.77\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"y3grid crisp\" transform=\"translate(0,71.6)\" d=\"M327.23,0h172.77\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"y3grid crisp\" transform=\"translate(0,20.5)\" d=\"M327.23,0h172.77\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/></g></g><g class=\"zerolinelayer\"/><path class=\"xlines-below\"/><path class=\"ylines-below\"/><g class=\"overlines-below\"/><g class=\"xaxislayer-below\"/><g class=\"yaxislayer-below\"/><g class=\"overaxes-below\"/><g class=\"plot\" transform=\"translate(327.23,10)\" clip-path=\"url(#clipbbcaffx3y3plot)\"><g class=\"scatterlayer mlayer\"><g class=\"trace scatter trace2ff438\" style=\"stroke-miterlimit: 2; opacity: 1;\"><g class=\"fills\"/><g class=\"errorbars\"/><g class=\"lines\"/><g class=\"points\"><path class=\"point\" transform=\"translate(14.89,136.68)\" d=\"M5,0A5,5 0 1,1 0,-5A5,5 0 0,1 5,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(50.64,124.67)\" d=\"M5,0A5,5 0 1,1 0,-5A5,5 0 0,1 5,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(86.39,104.74)\" d=\"M5,0A5,5 0 1,1 0,-5A5,5 0 0,1 5,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(122.13,99.63)\" d=\"M5,0A5,5 0 1,1 0,-5A5,5 0 0,1 5,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(157.88,105.79)\" d=\"M5,0A5,5 0 1,1 0,-5A5,5 0 0,1 5,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/></g><g class=\"text\"/></g></g></g><g class=\"overplot\"/><path class=\"xlines-above crisp\" d=\"M326.23,172.5H500\" style=\"fill: none; stroke-width: 1px; stroke: rgb(36, 36, 36); stroke-opacity: 1;\"/><path class=\"ylines-above crisp\" d=\"M326.73,10V172\" style=\"fill: none; stroke-width: 1px; stroke: rgb(36, 36, 36); stroke-opacity: 1;\"/><g class=\"overlines-above\"/><g class=\"xaxislayer-above\"><path class=\"x3tick ticks crisp\" d=\"M0,173v5\" transform=\"translate(342.12,0)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"x3tick ticks crisp\" d=\"M0,173v5\" transform=\"translate(377.87,0)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"x3tick ticks crisp\" d=\"M0,173v5\" transform=\"translate(413.62,0)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"x3tick ticks crisp\" d=\"M0,173v5\" transform=\"translate(449.36,0)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"x3tick ticks crisp\" d=\"M0,173v5\" transform=\"translate(485.11,0)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><g class=\"x3tick\"><text text-anchor=\"start\" x=\"0\" y=\"192.4\" transform=\"translate(342.12,0) rotate(45,0,186.4)\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\">Age_&#60;2</text></g><g class=\"x3tick\"><text text-anchor=\"start\" x=\"0\" y=\"192.4\" transform=\"translate(377.87,0) rotate(45,0,186.4)\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\">Age_2-5</text></g><g class=\"x3tick\"><text text-anchor=\"start\" x=\"0\" y=\"192.4\" transform=\"translate(413.62,0) rotate(45,0,186.4)\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\">Age_10-15</text></g><g class=\"x3tick\"><text text-anchor=\"start\" x=\"0\" y=\"192.4\" transform=\"translate(449.36,0) rotate(45,0,186.4)\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\">Age_15-20</text></g><g class=\"x3tick\"><text text-anchor=\"start\" x=\"0\" y=\"192.4\" transform=\"translate(485.11,0) rotate(45,0,186.4)\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\">Age_>20</text></g></g><g class=\"yaxislayer-above\"><path class=\"y3tick ticks crisp\" d=\"M326.23,0h-5\" transform=\"translate(0,122.71)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"y3tick ticks crisp\" d=\"M326.23,0h-5\" transform=\"translate(0,71.6)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"y3tick ticks crisp\" d=\"M326.23,0h-5\" transform=\"translate(0,20.5)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/></g><g class=\"overaxes-above\"/></g></g><g class=\"polarlayer\"/><g class=\"smithlayer\"/><g class=\"ternarylayer\"/><g class=\"geolayer\"/><g class=\"funnelarealayer\"/><g class=\"pielayer\"/><g class=\"iciclelayer\"/><g class=\"treemaplayer\"/><g class=\"sunburstlayer\"/><g class=\"glimages\"/><defs id=\"topdefs-bbcaff\"><g class=\"clips\"/></defs><g class=\"layer-above\"><g class=\"imagelayer\"/><g class=\"shapelayer\"/></g><g class=\"infolayer\"><g class=\"g-gtitle\"/><g class=\"g-xtitle\"/><g class=\"g-x2title\"/><g class=\"g-x3title\"/><g class=\"g-ytitle\" transform=\"translate(4.9248046875,0)\"><text class=\"ytitle\" transform=\"rotate(-90,10.075000000000003,91)\" x=\"10.075000000000003\" y=\"91\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(36, 36, 36); opacity: 1; font-weight: normal; white-space: pre;\">theta_hat</text></g><g class=\"g-y2title\"/><g class=\"g-y3title\"/></g></svg>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bcs_vars = ['BCS_1.5', 'BCS_2.0', 'BCS_2.5', 'BCS_3.5', 'BCS_4.0']\n",
    "age_vars = ['Age_<2', 'Age_2-5', 'Age_10-15', 'Age_15-20', 'Age_>20']\n",
    "sex_vars = ['Sex_gelding', 'Sex_stallion']\n",
    "\n",
    "thetas = (pd.DataFrame({'var': X_one_hot.columns, 'theta_hat': theta_hat})\n",
    "          .set_index('var'))\n",
    "\n",
    "f1 = px.scatter(thetas.loc[bcs_vars].reset_index(), x='var', y='theta_hat')\n",
    "f2 = px.scatter(thetas.loc[sex_vars].reset_index(), x='var', y='theta_hat')\n",
    "f3 = px.scatter(thetas.loc[age_vars].reset_index(), x='var', y='theta_hat')\n",
    "\n",
    "fig = plots_in_row([f1, f2, f3],\n",
    "                   width=550, height=250,\n",
    "                   shared_yaxes=True,\n",
    "                   column_widths=[0.35, 0.2, 0.45])\n",
    "\n",
    "ylabel(fig, 'theta_hat', row=1, col=1)\n",
    "fig.update_xaxes(tickangle=45)\n",
    "fig.update_traces(marker_size=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The coefficients confirm what we saw in the box plots. The coefficients for the\n",
    "sex of the donkey are close to zero, meaning that knowing the sex doesn't\n",
    "really change the weight prediction. We also see that combining the age\n",
    "categories for donkeys over 5 years will simplify the model without losing\n",
    "much. Lastly, since there are so few donkeys with a body condition score of 1.5 and its\n",
    "coefficient is close to that of a BCS of 2, we are inclined to combine these\n",
    "two categories. \n",
    "\n",
    "We update the design matrix in view of these findings:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "def combine_bcs(X):\n",
    "    new_bcs_2 = X['BCS_2.0'] + X['BCS_1.5']\n",
    "    return X.assign(**{'BCS_2.0': new_bcs_2}).drop(columns=['BCS_1.5'])\n",
    "\n",
    "def combine_age_and_sex(X):\n",
    "    return X.drop(columns=['Age_10-15', 'Age_15-20', 'Age_>20',\n",
    "                           'Sex_gelding', 'Sex_stallion'])\n",
    "\n",
    "X_one_hot_simple = (\n",
    "    X_one_hot.pipe(combine_bcs)\n",
    "    .pipe(combine_age_and_sex)\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And then we fit the simpler model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training error: 53.20\n"
     ]
    }
   ],
   "source": [
    "results = minimize(training_loss(X_one_hot_simple, y),\n",
    "                   np.ones(X_one_hot_simple.shape[1]))\n",
    "theta_hat = results['x']\n",
    "y_pred = X_one_hot_simple @ theta_hat\n",
    "training_error = (np.mean(anes_loss(100 * (y - y_pred)/ y_pred)))\n",
    "print(f'Training error: {training_error:.2f}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The average error is close enough to that of the more complex model for us to settle on this simpler one. Let's display the coefficients and summarize the model: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "tags": [
     "remove-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>var</th>\n",
       "      <th>theta_hat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>intr</td>\n",
       "      <td>-175.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Length</td>\n",
       "      <td>1.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Girth</td>\n",
       "      <td>1.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BCS_2.0</td>\n",
       "      <td>-6.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>BCS_2.5</td>\n",
       "      <td>-5.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>BCS_3.5</td>\n",
       "      <td>7.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>BCS_4.0</td>\n",
       "      <td>20.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Age_2-5</td>\n",
       "      <td>-3.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Age_&lt;2</td>\n",
       "      <td>-6.49</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       var  theta_hat\n",
       "0     intr    -175.25\n",
       "1   Length       1.01\n",
       "2    Girth       1.97\n",
       "3  BCS_2.0      -6.33\n",
       "4  BCS_2.5      -5.11\n",
       "5  BCS_3.5       7.36\n",
       "6  BCS_4.0      20.05\n",
       "7  Age_2-5      -3.47\n",
       "8   Age_<2      -6.49"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "thetas = pd.DataFrame({'var': X_one_hot_simple.columns, 'theta_hat': theta_hat})\n",
    "display_df(thetas, 9)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our model is roughly:\n",
    "\n",
    "$$\n",
    "\\text{Weight} \\approx -175 + \\text{Length} + 2\\text{Girth}\n",
    "$$\n",
    "\n",
    "After this initial approximation, we use the categorical features to make some adjustments: \n",
    "\n",
    "+ BCS 2 or less? Subtract 6.5 kg. \n",
    "+ BCS 2.5? Subtract 5.1 kg. \n",
    "+ BCS 3.5? Add 7.4 kg.\n",
    "+ BCS 4? Add 20 kg.\n",
    "+ Age under 2 years? Subtract 6.5 kg.\n",
    "+ Age between 2 and 5 years? Subtract 3.5 kg.\n",
    "\n",
    "This model seems quite simple to implement because after our initial estimate based on the length and girth of the donkey, we add or subtract a few numbers based on answers to a few yes/no questions. Let's see how well the model does in predicting the weights of the donkeys in the test set. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model Assessment\n",
    "\n",
    "Remember that we put aside 20\\% of our data before exploring and modeling with the remaining 80\\%. We are now ready to apply what we have learned from the training set to the test set. That is, we take our fitted model and use it to predict the weights of the donkeys in the test set.\n",
    "To do this, we need to prepare the test set. Our model uses the girth and length of the donkey, as well as dummy variables for the donkey's age and body condition score. We apply all of our transformations on the train set to our test set: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_test = test_set['Weight']\n",
    "\n",
    "X_test = (\n",
    "    test_set.assign(intr=1)\n",
    "    [['intr', 'Length', 'Girth', 'BCS', 'Age', 'Sex']]\n",
    "    .pipe(pd.get_dummies, columns=['BCS', 'Age', 'Sex'])\n",
    "    .drop(columns=['BCS_3.0', 'Age_5-10', 'Sex_female'])\n",
    "    .pipe(combine_bcs)\n",
    "    .pipe(combine_age_and_sex)\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We consolidate all of our manipulations of the design matrix to create the final version that we settled on in our modeling with the train set. Now we are ready to use the $\\theta$s that we fitted with the train set to make weight predictions for those donkeys in the test set: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred_test = X_test @ theta_hat\n",
    "test_set_error = 100 * (y_test - y_pred_test) / y_pred_test"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then we can plot the relative prediction errors:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "hovertemplate": "x=%{x}<br>y=%{y}<extra></extra>",
         "legendgroup": "",
         "marker": {
          "color": "#1F77B4",
          "size": 4,
          "symbol": "circle"
         },
         "mode": "markers",
         "name": "",
         "orientation": "v",
         "showlegend": false,
         "type": "scatter",
         "x": [
          165.9354635681202,
          156.9740967921392,
          140.29138675240344,
          153.07564266835547,
          169.93516835722,
          189.14409505906247,
          137.6058460417136,
          161.83667856168205,
          171.3226121724165,
          168.92258582678056,
          152.77406112038497,
          164.97350637033878,
          191.16926011994138,
          189.7818163047449,
          150.08852040969512,
          153.9363492008208,
          145.93693962262122,
          145.02560775749782,
          132.44385317217797,
          170.94775088765948,
          171.22136150710043,
          139.66060686000608,
          84.87181194165113,
          159.91059371814148,
          115.6855781486295,
          118.80137638204175,
          154.74643040062813,
          172.01095875075697,
          126.95316865553941,
          155.80963826372562,
          136.4941832939358,
          96.82247142427022,
          163.96092383989932,
          125.93841567712222,
          64.57119975085769,
          198.79042254211478,
          149.93664441172103,
          158.3615406073357,
          87.65860331765704,
          184.18243307218125,
          116.6475353464109,
          149.83539374640495,
          157.8854286572626,
          159.47765905011738,
          198.68917187679872,
          161.9357587790204,
          172.01095875075697,
          144.44079709149963,
          108.19199107696502,
          128.77532568846223,
          200.91683826830976,
          142.85073714662252,
          118.44115776938384,
          163.37382792687495,
          159.7587177201674,
          180.38522961371362,
          158.8495563030217,
          85.40884620343783,
          139.10198857283518,
          174.7375062955181,
          176.97262073763818,
          135.73255697880876,
          137.50676582437524,
          150.31379094350422,
          142.61813336125283,
          194.2070077112598,
          156.8728461268231,
          159.9612190507995,
          133.57709994533994,
          200.86621293565173,
          180.91831432281077,
          160.92317624858094,
          144.8252768748434,
          156.92564190745887,
          161.07505224655506,
          158.0879299878947,
          118.52082440931571,
          174.0361238116359,
          191.04413962720537,
          103.68646378133008,
          164.82380082034237,
          170.89712555500142,
          68.77174211993587,
          128.5432286004165,
          165.98608890077824,
          134.85132756842293,
          152.063060137916,
          142.1903614968116,
          132.06670664039473,
          173.2971519006374,
          158.7461351897279,
          138.56997368747273,
          154.8498515139219,
          160.92317624858094,
          173.9274250957108,
          169.88454302456196,
          108.59750043555329,
          158.03730465523668,
          153.0175692850884,
          135.42880498286056,
          156.2146409249899,
          152.01243480525795,
          104.56658389120189,
          152.97439200303938,
          150.89860160950244,
          147.96210468350014,
          170.94775088765948,
          176.28427415929775
         ],
         "xaxis": "x",
         "y": [
          10.283839310139037,
          -3.1687373227735502,
          5.494715980818756,
          1.9104001660017635,
          -4.6695268754137516,
          2.567304540710732,
          3.1932901723916394,
          5.044172625679908,
          0.9790813987212554,
          -2.3221204006449,
          3.4206977554239546,
          -1.8024144820343106,
          2.003847207262911,
          -6.2080849125324375,
          1.2735681483747938,
          5.887921109104007,
          7.58071287912901,
          -0.017657404022497256,
          5.705169886592613,
          10.560097467561178,
          9.799383876645425,
          10.26731407115217,
          -11.631437712721326,
          1.3066090452651964,
          -1.457033949784061,
          -4.041515787326802,
          -6.298323247518714,
          -4.075879119373909,
          -1.5384953965496717,
          3.973028758205887,
          -0.3620544714873288,
          3.281808994325339,
          9.172353880358516,
          0.0489003474806814,
          9.956141861924937,
          -7.94325115877728,
          0.7092032721227424,
          -0.22830076415596873,
          -0.7513276423882713,
          -3.8996298139717007,
          3.7312958569278636,
          16.127435347147305,
          -3.094287230183777,
          -7.824079638763796,
          -7.393040968486719,
          4.362372631124389,
          -4.075879119373909,
          0.3871502510098489,
          -2.0260197221120535,
          -2.155168836595604,
          -0.4563272427597083,
          -4.095699653700284,
          -5.43827660138664,
          -2.0650969434253907,
          8.288300299847155,
          1.4495479435238612,
          -8.089135784874252,
          7.717179296465972,
          7.834547542401603,
          8.162239468131704,
          -3.3748840429348603,
          -7.170392421273147,
          3.267645885413056,
          0.45651769687167104,
          -8.847495801456748,
          9.161869336452684,
          4.543268034682676,
          5.025456168002558,
          6.3056467449186515,
          -4.911833001407962,
          -1.6130563308276533,
          -1.8165041958067374,
          9.787464889437944,
          10.88054054455301,
          6.161691469299031,
          -8.911451993187253,
          0.4042965386651742,
          4.575990325424413,
          -3.163739876553984,
          6.089065041300741,
          12.241071422475962,
          10.007701644750133,
          4.694163301017079,
          -1.9785006399071194,
          4.225601763178163,
          4.559593548278018,
          -4.644823096095828,
          -0.1338779188741699,
          0.7066832991804233,
          2.7137480609370015,
          2.679665117634529,
          7.526902138302268,
          0.7427507839584232,
          1.2905684562246948,
          -5.132844973009922,
          8.308853015189982,
          -1.4710287337610646,
          13.897158897182932,
          0.6420378519287714,
          -1.0550229569266156,
          25.468393256502736,
          1.307501716743306,
          3.283473535264832,
          0.6704442381050542,
          4.706073028346986,
          0.7014602277522187,
          -4.649228109986921,
          0.40600662998191706
         ],
         "yaxis": "y"
        }
       ],
       "layout": {
        "height": 250,
        "legend": {
         "tracegroupgap": 0
        },
        "margin": {
         "t": 30
        },
        "shapes": [
         {
          "line": {
           "color": "green",
           "width": 3
          },
          "type": "line",
          "x0": 0,
          "x1": 1,
          "xref": "x domain",
          "y0": 10,
          "y1": 10,
          "yref": "y"
         },
         {
          "line": {
           "color": "green",
           "width": 3
          },
          "type": "line",
          "x0": 0,
          "x1": 1,
          "xref": "x domain",
          "y0": -10,
          "y1": -10,
          "yref": "y"
         }
        ],
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "rgb(36,36,36)"
            },
            "error_y": {
             "color": "rgb(36,36,36)"
            },
            "marker": {
             "line": {
              "color": "white",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "white",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "rgb(36,36,36)",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "rgb(36,36,36)"
            },
            "baxis": {
             "endlinecolor": "rgb(36,36,36)",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "rgb(36,36,36)"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "line": {
              "color": "white",
              "width": 0.6
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "parcoords"
           }
          ],
          "pie": [
           {
            "automargin": true,
            "type": "pie"
           }
          ],
          "scatter": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "rgb(237,237,237)"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "rgb(217,217,217)"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "autosize": true,
          "autotypenumbers": "strict",
          "coloraxis": {
           "colorbar": {
            "outlinewidth": 1,
            "tickcolor": "rgb(36,36,36)",
            "ticks": "outside"
           }
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "rgb(103,0,31)"
            ],
            [
             0.1,
             "rgb(178,24,43)"
            ],
            [
             0.2,
             "rgb(214,96,77)"
            ],
            [
             0.3,
             "rgb(244,165,130)"
            ],
            [
             0.4,
             "rgb(253,219,199)"
            ],
            [
             0.5,
             "rgb(247,247,247)"
            ],
            [
             0.6,
             "rgb(209,229,240)"
            ],
            [
             0.7,
             "rgb(146,197,222)"
            ],
            [
             0.8,
             "rgb(67,147,195)"
            ],
            [
             0.9,
             "rgb(33,102,172)"
            ],
            [
             1,
             "rgb(5,48,97)"
            ]
           ],
           "sequential": [
            [
             0,
             "#440154"
            ],
            [
             0.1111111111111111,
             "#482878"
            ],
            [
             0.2222222222222222,
             "#3e4989"
            ],
            [
             0.3333333333333333,
             "#31688e"
            ],
            [
             0.4444444444444444,
             "#26828e"
            ],
            [
             0.5555555555555556,
             "#1f9e89"
            ],
            [
             0.6666666666666666,
             "#35b779"
            ],
            [
             0.7777777777777778,
             "#6ece58"
            ],
            [
             0.8888888888888888,
             "#b5de2b"
            ],
            [
             1,
             "#fde725"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#440154"
            ],
            [
             0.1111111111111111,
             "#482878"
            ],
            [
             0.2222222222222222,
             "#3e4989"
            ],
            [
             0.3333333333333333,
             "#31688e"
            ],
            [
             0.4444444444444444,
             "#26828e"
            ],
            [
             0.5555555555555556,
             "#1f9e89"
            ],
            [
             0.6666666666666666,
             "#35b779"
            ],
            [
             0.7777777777777778,
             "#6ece58"
            ],
            [
             0.8888888888888888,
             "#b5de2b"
            ],
            [
             1,
             "#fde725"
            ]
           ]
          },
          "colorway": [
           "#1F77B4",
           "#FF7F0E",
           "#2CA02C",
           "#D62728",
           "#9467BD",
           "#8C564B",
           "#E377C2",
           "#7F7F7F",
           "#BCBD22",
           "#17BECF"
          ],
          "font": {
           "color": "rgb(36,36,36)"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "white",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "height": 250,
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "margin": {
           "b": 10,
           "l": 10,
           "r": 10,
           "t": 10
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "white",
          "polar": {
           "angularaxis": {
            "gridcolor": "rgb(232,232,232)",
            "linecolor": "rgb(36,36,36)",
            "showgrid": false,
            "showline": true,
            "ticks": "outside"
           },
           "bgcolor": "white",
           "radialaxis": {
            "gridcolor": "rgb(232,232,232)",
            "linecolor": "rgb(36,36,36)",
            "showgrid": false,
            "showline": true,
            "ticks": "outside"
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "white",
            "gridcolor": "rgb(232,232,232)",
            "gridwidth": 2,
            "linecolor": "rgb(36,36,36)",
            "showbackground": true,
            "showgrid": false,
            "showline": true,
            "ticks": "outside",
            "zeroline": false,
            "zerolinecolor": "rgb(36,36,36)"
           },
           "yaxis": {
            "backgroundcolor": "white",
            "gridcolor": "rgb(232,232,232)",
            "gridwidth": 2,
            "linecolor": "rgb(36,36,36)",
            "showbackground": true,
            "showgrid": false,
            "showline": true,
            "ticks": "outside",
            "zeroline": false,
            "zerolinecolor": "rgb(36,36,36)"
           },
           "zaxis": {
            "backgroundcolor": "white",
            "gridcolor": "rgb(232,232,232)",
            "gridwidth": 2,
            "linecolor": "rgb(36,36,36)",
            "showbackground": true,
            "showgrid": false,
            "showline": true,
            "ticks": "outside",
            "zeroline": false,
            "zerolinecolor": "rgb(36,36,36)"
           }
          },
          "shapedefaults": {
           "fillcolor": "black",
           "line": {
            "width": 0
           },
           "opacity": 0.3
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "rgb(232,232,232)",
            "linecolor": "rgb(36,36,36)",
            "showgrid": false,
            "showline": true,
            "ticks": "outside"
           },
           "baxis": {
            "gridcolor": "rgb(232,232,232)",
            "linecolor": "rgb(36,36,36)",
            "showgrid": false,
            "showline": true,
            "ticks": "outside"
           },
           "bgcolor": "white",
           "caxis": {
            "gridcolor": "rgb(232,232,232)",
            "linecolor": "rgb(36,36,36)",
            "showgrid": false,
            "showline": true,
            "ticks": "outside"
           }
          },
          "title": {
           "x": 0.5,
           "xanchor": "center"
          },
          "width": 350,
          "xaxis": {
           "automargin": true,
           "gridcolor": "rgb(232,232,232)",
           "linecolor": "rgb(36,36,36)",
           "showgrid": true,
           "showline": true,
           "ticks": "outside",
           "title": {
            "standoff": 15
           },
           "zeroline": false,
           "zerolinecolor": "rgb(36,36,36)"
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "rgb(232,232,232)",
           "linecolor": "rgb(36,36,36)",
           "showgrid": true,
           "showline": true,
           "ticks": "outside",
           "title": {
            "standoff": 15
           },
           "zeroline": false,
           "zerolinecolor": "rgb(36,36,36)"
          }
         }
        },
        "title": {
         "text": "Test set predictions"
        },
        "width": 350,
        "xaxis": {
         "anchor": "y",
         "autorange": true,
         "domain": [
          0,
          1
         ],
         "range": [
          55.12150203182635,
          210.36653598734108
         ],
         "title": {
          "text": "Predicted weight (kg)"
         },
         "type": "linear"
        },
        "yaxis": {
         "anchor": "x",
         "autorange": true,
         "domain": [
          0,
          1
         ],
         "range": [
          -14.582864150517768,
          28.41981969429918
         ],
         "title": {
          "text": "Relative error (%)"
         },
         "type": "linear"
        }
       }
      },
      "image/png": "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",
      "image/svg+xml": [
       "<svg class=\"main-svg\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"350\" height=\"250\" style=\"\" viewBox=\"0 0 350 250\"><rect x=\"0\" y=\"0\" width=\"350\" height=\"250\" style=\"fill: rgb(255, 255, 255); fill-opacity: 1;\"/><defs id=\"defs-b09944\"><g class=\"clips\"><clipPath id=\"clipb09944xyplot\" class=\"plotclip\"><rect width=\"276\" height=\"161\"/></clipPath><clipPath class=\"axesclip\" id=\"clipb09944x\"><rect x=\"64\" y=\"0\" width=\"276\" height=\"250\"/></clipPath><clipPath class=\"axesclip\" id=\"clipb09944y\"><rect x=\"0\" y=\"30\" width=\"350\" height=\"161\"/></clipPath><clipPath class=\"axesclip\" id=\"clipb09944xy\"><rect x=\"64\" y=\"30\" width=\"276\" height=\"161\"/></clipPath></g><g class=\"gradients\"/><g class=\"patterns\"/></defs><g class=\"bglayer\"/><g class=\"layer-below\"><g class=\"imagelayer\"/><g class=\"shapelayer\"/></g><g class=\"cartesianlayer\"><g class=\"subplot xy\"><g class=\"layer-subplot\"><g class=\"shapelayer\"/><g class=\"imagelayer\"/></g><g class=\"gridlayer\"><g class=\"x\"><path class=\"xgrid crisp\" transform=\"translate(143.79000000000002,0)\" d=\"M0,30v161\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"xgrid crisp\" transform=\"translate(232.68,0)\" d=\"M0,30v161\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"xgrid crisp\" transform=\"translate(321.57,0)\" d=\"M0,30v161\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/></g><g class=\"y\"><path class=\"ygrid crisp\" transform=\"translate(0,173.84)\" d=\"M64,0h276\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"ygrid crisp\" transform=\"translate(0,136.4)\" d=\"M64,0h276\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"ygrid crisp\" transform=\"translate(0,98.96)\" d=\"M64,0h276\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"ygrid crisp\" transform=\"translate(0,61.519999999999996)\" d=\"M64,0h276\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/></g></g><g class=\"zerolinelayer\"/><path class=\"xlines-below\"/><path class=\"ylines-below\"/><g class=\"overlines-below\"/><g class=\"xaxislayer-below\"/><g class=\"yaxislayer-below\"/><g class=\"overaxes-below\"/><g class=\"plot\" transform=\"translate(64,30)\" clip-path=\"url(#clipb09944xyplot)\"><g class=\"scatterlayer mlayer\"><g class=\"trace scatter tracedfb3e6\" style=\"stroke-miterlimit: 2; opacity: 1;\"><g class=\"fills\"/><g class=\"errorbars\"/><g class=\"lines\"/><g class=\"points\"><path class=\"point\" transform=\"translate(197.01,67.9)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.08,118.27)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(151.42,85.83)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(174.15,99.25)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(204.12,123.88)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(238.27,96.79)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(146.64,94.45)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(189.72,87.52)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(206.59,102.74)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(202.32,115.1)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(173.61,93.6)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(195.3,113.15)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(241.87,98.9)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(239.4,129.65)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(168.84,101.63)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(175.68,84.36)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(161.45,78.02)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.83,106.47)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(137.47,85.04)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(205.92,66.87)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(206.41,69.71)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(150.3,67.96)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(52.89,149.95)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(186.3,101.51)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(107.67,111.86)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(113.21,121.53)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(177.12,129.98)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(207.81,121.66)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(127.7,112.16)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(179.01,91.53)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(144.67,107.76)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(74.14,94.12)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(193.5,72.06)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(125.9,106.22)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(16.8,69.13)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(255.42,136.14)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(168.57,103.75)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(183.54,107.26)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(57.85,109.22)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(229.45,121)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(109.38,92.43)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(168.39,46.02)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(182.7,117.99)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(185.53,135.7)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(255.24,134.08)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(189.9,90.07)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(207.81,121.66)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(158.79,104.95)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(94.35,113.99)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(130.94,114.47)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(259.2,108.11)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(155.97,121.74)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(112.57,126.76)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(192.45,114.13)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(186.03,75.37)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(222.7,100.98)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(184.41,136.69)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(53.85,77.51)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(149.3,77.07)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(212.66,75.84)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(216.63,119.04)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(143.31,133.25)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(146.47,94.17)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(169.24,104.69)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(155.55,139.53)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(247.27,72.1)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(180.9,89.39)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(186.39,87.59)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(139.48,82.79)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(259.11,124.79)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(223.65,112.44)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(188.1,113.2)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.48,69.76)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(180.99,65.67)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(188.37,83.33)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(183.06,139.77)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(112.71,104.89)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(211.41,89.27)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(241.65,118.25)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(86.34,83.61)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(195.03,60.57)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(205.83,68.93)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(24.27,88.83)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(130.53,113.81)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(197.1,90.58)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(141.75,89.33)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(172.35,123.79)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.79,106.9)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(136.8,103.76)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(210.1,96.24)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(184.23,96.37)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(148.36,78.22)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(177.3,103.62)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(188.1,101.57)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(211.22,125.62)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(204.03,75.29)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(95.07,111.91)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(182.97,54.37)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(174.04,104)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(142.77,110.35)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(179.73,11.05)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(172.26,101.51)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(87.91,94.11)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(173.97,103.89)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.28,88.78)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(165.06,103.78)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(205.92,123.81)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(215.41,104.88)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/></g><g class=\"text\"/></g></g></g><g class=\"overplot\"/><path class=\"xlines-above crisp\" d=\"M63,191.5H340\" style=\"fill: none; stroke-width: 1px; stroke: rgb(36, 36, 36); stroke-opacity: 1;\"/><path class=\"ylines-above crisp\" d=\"M63.5,30V191\" style=\"fill: none; stroke-width: 1px; stroke: rgb(36, 36, 36); stroke-opacity: 1;\"/><g class=\"overlines-above\"/><g class=\"xaxislayer-above\"><path class=\"xtick ticks crisp\" d=\"M0,192v5\" transform=\"translate(143.79000000000002,0)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"xtick ticks crisp\" d=\"M0,192v5\" transform=\"translate(232.68,0)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"xtick ticks crisp\" d=\"M0,192v5\" transform=\"translate(321.57,0)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><g class=\"xtick\"><text text-anchor=\"middle\" x=\"0\" y=\"211.4\" transform=\"translate(143.79000000000002,0)\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\">100</text></g><g class=\"xtick\"><text text-anchor=\"middle\" x=\"0\" y=\"211.4\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(232.68,0)\">150</text></g><g class=\"xtick\"><text text-anchor=\"middle\" x=\"0\" y=\"211.4\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(321.57,0)\">200</text></g></g><g class=\"yaxislayer-above\"><path class=\"ytick ticks crisp\" d=\"M63,0h-5\" transform=\"translate(0,173.84)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"ytick ticks crisp\" d=\"M63,0h-5\" transform=\"translate(0,136.4)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"ytick ticks crisp\" d=\"M63,0h-5\" transform=\"translate(0,98.96)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"ytick ticks crisp\" d=\"M63,0h-5\" transform=\"translate(0,61.519999999999996)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><g class=\"ytick\"><text text-anchor=\"end\" x=\"55.6\" y=\"4.199999999999999\" transform=\"translate(0,173.84)\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\">−10</text></g><g class=\"ytick\"><text text-anchor=\"end\" x=\"55.6\" y=\"4.199999999999999\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(0,136.4)\">0</text></g><g class=\"ytick\"><text text-anchor=\"end\" x=\"55.6\" y=\"4.199999999999999\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(0,98.96)\">10</text></g><g class=\"ytick\"><text text-anchor=\"end\" x=\"55.6\" y=\"4.199999999999999\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(0,61.519999999999996)\">20</text></g></g><g class=\"overaxes-above\"/></g></g><g class=\"polarlayer\"/><g class=\"smithlayer\"/><g class=\"ternarylayer\"/><g class=\"geolayer\"/><g class=\"funnelarealayer\"/><g class=\"pielayer\"/><g class=\"iciclelayer\"/><g class=\"treemaplayer\"/><g class=\"sunburstlayer\"/><g class=\"glimages\"/><defs id=\"topdefs-b09944\"><g class=\"clips\"/></defs><g class=\"layer-above\"><g class=\"imagelayer\"/><g class=\"shapelayer\"><path data-index=\"0\" fill-rule=\"evenodd\" d=\"M64,98.96L340,98.96\" clip-path=\"url(#clipb09944y)\" style=\"opacity: 0.3; stroke: rgb(0, 128, 0); stroke-opacity: 1; fill: rgb(0, 0, 0); fill-opacity: 1; stroke-width: 3px;\"/><path data-index=\"1\" fill-rule=\"evenodd\" d=\"M64,173.84L340,173.84\" clip-path=\"url(#clipb09944y)\" style=\"opacity: 0.3; stroke: rgb(0, 128, 0); stroke-opacity: 1; fill: rgb(0, 0, 0); fill-opacity: 1; stroke-width: 3px;\"/></g></g><g class=\"infolayer\"><g class=\"g-gtitle\"><text class=\"gtitle\" x=\"175\" y=\"15\" text-anchor=\"middle\" dy=\"0em\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 17px; fill: rgb(36, 36, 36); opacity: 1; font-weight: normal; white-space: pre;\">Test set predictions</text></g><g class=\"g-xtitle\"><text class=\"xtitle\" x=\"202\" y=\"239.70625\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(36, 36, 36); opacity: 1; font-weight: normal; white-space: pre;\">Predicted weight (kg)</text></g><g class=\"g-ytitle\" transform=\"translate(4.7841796875,0)\"><text class=\"ytitle\" transform=\"rotate(-90,10.215625000000003,110.5)\" x=\"10.215625000000003\" y=\"110.5\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(36, 36, 36); opacity: 1; font-weight: normal; white-space: pre;\">Relative error (%)</text></g></g></svg>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = px.scatter(x=y_pred_test, y=test_set_error,\n",
    "                 title='Test set predictions',\n",
    "                 width=350, height=250)\n",
    "fig.update_traces(marker=dict(size=4))\n",
    "fig.add_hline(10, line_width=3, line_color='green')\n",
    "fig.add_hline(-10, line_width=3, line_color='green')\n",
    "margin(fig, t=30)\n",
    "xlabel(fig, 'Predicted weight (kg)')\n",
    "ylabel(fig, 'Relative error (%)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Remember that positive relative error means underestimating weight, which is not as critical as overestimating weight. From this residual plot, we see that\n",
    "nearly all of the test set weights are within 10% of the predictions, \n",
    "and only one error that exceeds 10% errs on the side of overestimation.\n",
    "This makes sense given that our loss function penalized overestimation more. \n",
    "\n",
    "An alternative scatter plot that shows the actual and predicted values along with lines marking 10% error gives a different view:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "hovertemplate": "x=%{x}<br>y=%{y}<extra></extra>",
         "legendgroup": "",
         "marker": {
          "color": "#1F77B4",
          "size": 4,
          "symbol": "circle"
         },
         "mode": "markers",
         "name": "",
         "orientation": "v",
         "showlegend": false,
         "type": "scatter",
         "x": [
          165.9354635681202,
          156.9740967921392,
          140.29138675240344,
          153.07564266835547,
          169.93516835722,
          189.14409505906247,
          137.6058460417136,
          161.83667856168205,
          171.3226121724165,
          168.92258582678056,
          152.77406112038497,
          164.97350637033878,
          191.16926011994138,
          189.7818163047449,
          150.08852040969512,
          153.9363492008208,
          145.93693962262122,
          145.02560775749782,
          132.44385317217797,
          170.94775088765948,
          171.22136150710043,
          139.66060686000608,
          84.87181194165113,
          159.91059371814148,
          115.6855781486295,
          118.80137638204175,
          154.74643040062813,
          172.01095875075697,
          126.95316865553941,
          155.80963826372562,
          136.4941832939358,
          96.82247142427022,
          163.96092383989932,
          125.93841567712222,
          64.57119975085769,
          198.79042254211478,
          149.93664441172103,
          158.3615406073357,
          87.65860331765704,
          184.18243307218125,
          116.6475353464109,
          149.83539374640495,
          157.8854286572626,
          159.47765905011738,
          198.68917187679872,
          161.9357587790204,
          172.01095875075697,
          144.44079709149963,
          108.19199107696502,
          128.77532568846223,
          200.91683826830976,
          142.85073714662252,
          118.44115776938384,
          163.37382792687495,
          159.7587177201674,
          180.38522961371362,
          158.8495563030217,
          85.40884620343783,
          139.10198857283518,
          174.7375062955181,
          176.97262073763818,
          135.73255697880876,
          137.50676582437524,
          150.31379094350422,
          142.61813336125283,
          194.2070077112598,
          156.8728461268231,
          159.9612190507995,
          133.57709994533994,
          200.86621293565173,
          180.91831432281077,
          160.92317624858094,
          144.8252768748434,
          156.92564190745887,
          161.07505224655506,
          158.0879299878947,
          118.52082440931571,
          174.0361238116359,
          191.04413962720537,
          103.68646378133008,
          164.82380082034237,
          170.89712555500142,
          68.77174211993587,
          128.5432286004165,
          165.98608890077824,
          134.85132756842293,
          152.063060137916,
          142.1903614968116,
          132.06670664039473,
          173.2971519006374,
          158.7461351897279,
          138.56997368747273,
          154.8498515139219,
          160.92317624858094,
          173.9274250957108,
          169.88454302456196,
          108.59750043555329,
          158.03730465523668,
          153.0175692850884,
          135.42880498286056,
          156.2146409249899,
          152.01243480525795,
          104.56658389120189,
          152.97439200303938,
          150.89860160950244,
          147.96210468350014,
          170.94775088765948,
          176.28427415929775
         ],
         "xaxis": "x",
         "y": [
          183,
          152,
          148,
          156,
          162,
          194,
          142,
          170,
          173,
          165,
          158,
          162,
          195,
          178,
          152,
          163,
          157,
          145,
          140,
          189,
          188,
          154,
          75,
          162,
          114,
          114,
          145,
          165,
          125,
          162,
          136,
          100,
          179,
          126,
          71,
          183,
          151,
          158,
          87,
          177,
          121,
          174,
          153,
          147,
          184,
          169,
          165,
          145,
          106,
          126,
          200,
          137,
          112,
          160,
          173,
          183,
          146,
          92,
          150,
          189,
          171,
          126,
          142,
          151,
          130,
          212,
          164,
          168,
          142,
          191,
          178,
          158,
          159,
          174,
          171,
          144,
          119,
          182,
          185,
          110,
          185,
          188,
          72,
          126,
          173,
          141,
          145,
          142,
          133,
          178,
          163,
          149,
          156,
          163,
          165,
          184,
          107,
          180,
          154,
          134,
          196,
          154,
          108,
          154,
          158,
          149,
          163,
          177
         ],
         "yaxis": "y"
        },
        {
         "marker": {
          "color": "green"
         },
         "mode": "lines",
         "name": "0% error",
         "type": "scatter",
         "x": [
          60,
          200
         ],
         "y": [
          60,
          200
         ]
        },
        {
         "marker": {
          "color": "red"
         },
         "mode": "lines",
         "name": "10% error",
         "type": "scatter",
         "x": [
          60,
          200
         ],
         "y": [
          66,
          220
         ]
        },
        {
         "marker": {
          "color": "red"
         },
         "mode": "lines",
         "name": "-10% error",
         "type": "scatter",
         "x": [
          60,
          200
         ],
         "y": [
          54,
          180
         ]
        }
       ],
       "layout": {
        "height": 350,
        "legend": {
         "tracegroupgap": 0
        },
        "margin": {
         "t": 30
        },
        "showlegend": false,
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "rgb(36,36,36)"
            },
            "error_y": {
             "color": "rgb(36,36,36)"
            },
            "marker": {
             "line": {
              "color": "white",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "white",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "rgb(36,36,36)",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "rgb(36,36,36)"
            },
            "baxis": {
             "endlinecolor": "rgb(36,36,36)",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "rgb(36,36,36)"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "line": {
              "color": "white",
              "width": 0.6
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "parcoords"
           }
          ],
          "pie": [
           {
            "automargin": true,
            "type": "pie"
           }
          ],
          "scatter": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 1,
              "tickcolor": "rgb(36,36,36)",
              "ticks": "outside"
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 1,
             "tickcolor": "rgb(36,36,36)",
             "ticks": "outside"
            },
            "colorscale": [
             [
              0,
              "#440154"
             ],
             [
              0.1111111111111111,
              "#482878"
             ],
             [
              0.2222222222222222,
              "#3e4989"
             ],
             [
              0.3333333333333333,
              "#31688e"
             ],
             [
              0.4444444444444444,
              "#26828e"
             ],
             [
              0.5555555555555556,
              "#1f9e89"
             ],
             [
              0.6666666666666666,
              "#35b779"
             ],
             [
              0.7777777777777778,
              "#6ece58"
             ],
             [
              0.8888888888888888,
              "#b5de2b"
             ],
             [
              1,
              "#fde725"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "rgb(237,237,237)"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "rgb(217,217,217)"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "autosize": true,
          "autotypenumbers": "strict",
          "coloraxis": {
           "colorbar": {
            "outlinewidth": 1,
            "tickcolor": "rgb(36,36,36)",
            "ticks": "outside"
           }
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "rgb(103,0,31)"
            ],
            [
             0.1,
             "rgb(178,24,43)"
            ],
            [
             0.2,
             "rgb(214,96,77)"
            ],
            [
             0.3,
             "rgb(244,165,130)"
            ],
            [
             0.4,
             "rgb(253,219,199)"
            ],
            [
             0.5,
             "rgb(247,247,247)"
            ],
            [
             0.6,
             "rgb(209,229,240)"
            ],
            [
             0.7,
             "rgb(146,197,222)"
            ],
            [
             0.8,
             "rgb(67,147,195)"
            ],
            [
             0.9,
             "rgb(33,102,172)"
            ],
            [
             1,
             "rgb(5,48,97)"
            ]
           ],
           "sequential": [
            [
             0,
             "#440154"
            ],
            [
             0.1111111111111111,
             "#482878"
            ],
            [
             0.2222222222222222,
             "#3e4989"
            ],
            [
             0.3333333333333333,
             "#31688e"
            ],
            [
             0.4444444444444444,
             "#26828e"
            ],
            [
             0.5555555555555556,
             "#1f9e89"
            ],
            [
             0.6666666666666666,
             "#35b779"
            ],
            [
             0.7777777777777778,
             "#6ece58"
            ],
            [
             0.8888888888888888,
             "#b5de2b"
            ],
            [
             1,
             "#fde725"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#440154"
            ],
            [
             0.1111111111111111,
             "#482878"
            ],
            [
             0.2222222222222222,
             "#3e4989"
            ],
            [
             0.3333333333333333,
             "#31688e"
            ],
            [
             0.4444444444444444,
             "#26828e"
            ],
            [
             0.5555555555555556,
             "#1f9e89"
            ],
            [
             0.6666666666666666,
             "#35b779"
            ],
            [
             0.7777777777777778,
             "#6ece58"
            ],
            [
             0.8888888888888888,
             "#b5de2b"
            ],
            [
             1,
             "#fde725"
            ]
           ]
          },
          "colorway": [
           "#1F77B4",
           "#FF7F0E",
           "#2CA02C",
           "#D62728",
           "#9467BD",
           "#8C564B",
           "#E377C2",
           "#7F7F7F",
           "#BCBD22",
           "#17BECF"
          ],
          "font": {
           "color": "rgb(36,36,36)"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "white",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "height": 250,
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "margin": {
           "b": 10,
           "l": 10,
           "r": 10,
           "t": 10
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "white",
          "polar": {
           "angularaxis": {
            "gridcolor": "rgb(232,232,232)",
            "linecolor": "rgb(36,36,36)",
            "showgrid": false,
            "showline": true,
            "ticks": "outside"
           },
           "bgcolor": "white",
           "radialaxis": {
            "gridcolor": "rgb(232,232,232)",
            "linecolor": "rgb(36,36,36)",
            "showgrid": false,
            "showline": true,
            "ticks": "outside"
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "white",
            "gridcolor": "rgb(232,232,232)",
            "gridwidth": 2,
            "linecolor": "rgb(36,36,36)",
            "showbackground": true,
            "showgrid": false,
            "showline": true,
            "ticks": "outside",
            "zeroline": false,
            "zerolinecolor": "rgb(36,36,36)"
           },
           "yaxis": {
            "backgroundcolor": "white",
            "gridcolor": "rgb(232,232,232)",
            "gridwidth": 2,
            "linecolor": "rgb(36,36,36)",
            "showbackground": true,
            "showgrid": false,
            "showline": true,
            "ticks": "outside",
            "zeroline": false,
            "zerolinecolor": "rgb(36,36,36)"
           },
           "zaxis": {
            "backgroundcolor": "white",
            "gridcolor": "rgb(232,232,232)",
            "gridwidth": 2,
            "linecolor": "rgb(36,36,36)",
            "showbackground": true,
            "showgrid": false,
            "showline": true,
            "ticks": "outside",
            "zeroline": false,
            "zerolinecolor": "rgb(36,36,36)"
           }
          },
          "shapedefaults": {
           "fillcolor": "black",
           "line": {
            "width": 0
           },
           "opacity": 0.3
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "rgb(232,232,232)",
            "linecolor": "rgb(36,36,36)",
            "showgrid": false,
            "showline": true,
            "ticks": "outside"
           },
           "baxis": {
            "gridcolor": "rgb(232,232,232)",
            "linecolor": "rgb(36,36,36)",
            "showgrid": false,
            "showline": true,
            "ticks": "outside"
           },
           "bgcolor": "white",
           "caxis": {
            "gridcolor": "rgb(232,232,232)",
            "linecolor": "rgb(36,36,36)",
            "showgrid": false,
            "showline": true,
            "ticks": "outside"
           }
          },
          "title": {
           "x": 0.5,
           "xanchor": "center"
          },
          "width": 350,
          "xaxis": {
           "automargin": true,
           "gridcolor": "rgb(232,232,232)",
           "linecolor": "rgb(36,36,36)",
           "showgrid": true,
           "showline": true,
           "ticks": "outside",
           "title": {
            "standoff": 15
           },
           "zeroline": false,
           "zerolinecolor": "rgb(36,36,36)"
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "rgb(232,232,232)",
           "linecolor": "rgb(36,36,36)",
           "showgrid": true,
           "showline": true,
           "ticks": "outside",
           "title": {
            "standoff": 15
           },
           "zeroline": false,
           "zerolinecolor": "rgb(36,36,36)"
          }
         }
        },
        "title": {
         "text": "Test set predictions with 10% error lines"
        },
        "width": 350,
        "xaxis": {
         "anchor": "y",
         "autorange": true,
         "domain": [
          0,
          1
         ],
         "range": [
          55.12150203182635,
          210.36653598734108
         ],
         "title": {
          "text": "Predicted weight (kg)"
         },
         "type": "linear"
        },
        "yaxis": {
         "anchor": "x",
         "autorange": true,
         "domain": [
          0,
          1
         ],
         "range": [
          44.77777777777778,
          229.22222222222223
         ],
         "title": {
          "text": "Actual weight (kg)"
         },
         "type": "linear"
        }
       }
      },
      "image/png": "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",
      "image/svg+xml": [
       "<svg class=\"main-svg\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"350\" height=\"350\" style=\"\" viewBox=\"0 0 350 350\"><rect x=\"0\" y=\"0\" width=\"350\" height=\"350\" style=\"fill: rgb(255, 255, 255); fill-opacity: 1;\"/><defs id=\"defs-d475f1\"><g class=\"clips\"><clipPath id=\"clipd475f1xyplot\" class=\"plotclip\"><rect width=\"276\" height=\"261\"/></clipPath><clipPath class=\"axesclip\" id=\"clipd475f1x\"><rect x=\"64\" y=\"0\" width=\"276\" height=\"350\"/></clipPath><clipPath class=\"axesclip\" id=\"clipd475f1y\"><rect x=\"0\" y=\"30\" width=\"350\" height=\"261\"/></clipPath><clipPath class=\"axesclip\" id=\"clipd475f1xy\"><rect x=\"64\" y=\"30\" width=\"276\" height=\"261\"/></clipPath></g><g class=\"gradients\"/><g class=\"patterns\"/></defs><g class=\"bglayer\"/><g class=\"layer-below\"><g class=\"imagelayer\"/><g class=\"shapelayer\"/></g><g class=\"cartesianlayer\"><g class=\"subplot xy\"><g class=\"layer-subplot\"><g class=\"shapelayer\"/><g class=\"imagelayer\"/></g><g class=\"gridlayer\"><g class=\"x\"><path class=\"xgrid crisp\" transform=\"translate(143.79000000000002,0)\" d=\"M0,30v261\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"xgrid crisp\" transform=\"translate(232.68,0)\" d=\"M0,30v261\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"xgrid crisp\" transform=\"translate(321.57,0)\" d=\"M0,30v261\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/></g><g class=\"y\"><path class=\"ygrid crisp\" transform=\"translate(0,283.61)\" d=\"M64,0h276\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"ygrid crisp\" transform=\"translate(0,212.86)\" d=\"M64,0h276\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"ygrid crisp\" transform=\"translate(0,142.1)\" d=\"M64,0h276\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"ygrid crisp\" transform=\"translate(0,71.35)\" d=\"M64,0h276\" style=\"stroke: rgb(232, 232, 232); stroke-opacity: 1; stroke-width: 1px;\"/></g></g><g class=\"zerolinelayer\"/><path class=\"xlines-below\"/><path class=\"ylines-below\"/><g class=\"overlines-below\"/><g class=\"xaxislayer-below\"/><g class=\"yaxislayer-below\"/><g class=\"overaxes-below\"/><g class=\"plot\" transform=\"translate(64,30)\" clip-path=\"url(#clipd475f1xyplot)\"><g class=\"scatterlayer mlayer\"><g class=\"trace scatter trace6dcfaf\" style=\"stroke-miterlimit: 2; opacity: 1;\"><g class=\"fills\"/><g class=\"errorbars\"/><g class=\"lines\"/><g class=\"points\"><path class=\"point\" transform=\"translate(197.01,65.41)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(181.08,109.27)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(151.42,114.93)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(174.15,103.61)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(204.12,95.12)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(238.27,49.84)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(146.64,123.42)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(189.72,83.8)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(206.59,79.56)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(202.32,90.88)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(173.61,100.78)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(195.3,95.12)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(241.87,48.43)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(239.4,72.48)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(168.84,109.27)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(175.68,93.71)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(161.45,102.2)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.83,119.18)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(137.47,126.25)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(205.92,56.92)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(206.41,58.33)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(150.3,106.44)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(52.89,218.23)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(186.3,95.12)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(107.67,163.05)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(113.21,163.05)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(177.12,119.18)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(207.81,90.88)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(127.7,147.48)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(179.01,95.12)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(144.67,131.92)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(74.14,182.86)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(193.5,71.07)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(125.9,146.07)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(16.8,223.89)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(255.42,65.41)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(168.57,110.69)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(183.54,100.78)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(57.85,201.25)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(229.45,73.9)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(109.38,153.14)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(168.39,78.14)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(182.7,107.86)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(185.53,116.35)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(255.24,63.99)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(189.9,85.22)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(207.81,90.88)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(158.79,119.18)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(94.35,174.37)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(130.94,146.07)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(259.2,41.35)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(155.97,130.5)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(112.57,165.88)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(192.45,97.95)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(186.03,79.56)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(222.7,65.41)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(184.41,117.76)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(53.85,194.18)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(149.3,112.1)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(212.66,56.92)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(216.63,82.39)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(143.31,146.07)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(146.47,123.42)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(169.24,110.69)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(155.55,140.41)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(247.27,24.37)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(180.9,92.29)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(186.39,86.63)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(139.48,123.42)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(259.11,54.09)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(223.65,72.48)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(188.1,100.78)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(159.48,99.37)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(180.99,78.14)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(188.37,82.39)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(183.06,120.59)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(112.71,155.97)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(211.41,66.82)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(241.65,62.58)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(86.34,168.71)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(195.03,62.58)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(205.83,58.33)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(24.27,222.48)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(130.53,146.07)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(197.1,79.56)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(141.75,124.84)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(172.35,119.18)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(154.79,123.42)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(136.8,136.16)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(210.1,72.48)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(184.23,93.71)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(148.36,113.52)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(177.3,103.61)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(188.1,93.71)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(211.22,90.88)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(204.03,63.99)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(95.07,172.95)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(182.97,69.65)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(174.04,106.44)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(142.77,134.75)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(179.73,47.01)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(172.26,106.44)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(87.91,171.54)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(173.97,106.44)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(170.28,100.78)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(165.06,113.52)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(205.92,93.71)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(215.41,73.9)\" d=\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/></g><g class=\"text\"/></g><g class=\"trace scatter trace2272a1\" style=\"stroke-miterlimit: 2; opacity: 1;\"><g class=\"fills\"/><g class=\"errorbars\"/><g class=\"lines\"><path class=\"js-line\" d=\"M8.67,239.46L257.57,41.35\" style=\"vector-effect: non-scaling-stroke; fill: none; stroke: rgb(0, 128, 0); stroke-opacity: 1; stroke-width: 2px; opacity: 1;\"/></g><g class=\"points\"/><g class=\"text\"/></g><g class=\"trace scatter trace87ff06\" style=\"stroke-miterlimit: 2; opacity: 1;\"><g class=\"fills\"/><g class=\"errorbars\"/><g class=\"lines\"><path class=\"js-line\" d=\"M8.67,230.97L257.57,13.05\" style=\"vector-effect: non-scaling-stroke; fill: none; stroke: rgb(255, 0, 0); stroke-opacity: 1; stroke-width: 2px; opacity: 1;\"/></g><g class=\"points\"/><g class=\"text\"/></g><g class=\"trace scatter trace095623\" style=\"stroke-miterlimit: 2; opacity: 1;\"><g class=\"fills\"/><g class=\"errorbars\"/><g class=\"lines\"><path class=\"js-line\" d=\"M8.67,247.95L257.57,69.65\" style=\"vector-effect: non-scaling-stroke; fill: none; stroke: rgb(255, 0, 0); stroke-opacity: 1; stroke-width: 2px; opacity: 1;\"/></g><g class=\"points\"/><g class=\"text\"/></g></g></g><g class=\"overplot\"/><path class=\"xlines-above crisp\" d=\"M63,291.5H340\" style=\"fill: none; stroke-width: 1px; stroke: rgb(36, 36, 36); stroke-opacity: 1;\"/><path class=\"ylines-above crisp\" d=\"M63.5,30V291\" style=\"fill: none; stroke-width: 1px; stroke: rgb(36, 36, 36); stroke-opacity: 1;\"/><g class=\"overlines-above\"/><g class=\"xaxislayer-above\"><path class=\"xtick ticks crisp\" d=\"M0,292v5\" transform=\"translate(143.79000000000002,0)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"xtick ticks crisp\" d=\"M0,292v5\" transform=\"translate(232.68,0)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"xtick ticks crisp\" d=\"M0,292v5\" transform=\"translate(321.57,0)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><g class=\"xtick\"><text text-anchor=\"middle\" x=\"0\" y=\"311.4\" transform=\"translate(143.79000000000002,0)\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\">100</text></g><g class=\"xtick\"><text text-anchor=\"middle\" x=\"0\" y=\"311.4\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(232.68,0)\">150</text></g><g class=\"xtick\"><text text-anchor=\"middle\" x=\"0\" y=\"311.4\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(321.57,0)\">200</text></g></g><g class=\"yaxislayer-above\"><path class=\"ytick ticks crisp\" d=\"M63,0h-5\" transform=\"translate(0,283.61)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"ytick ticks crisp\" d=\"M63,0h-5\" transform=\"translate(0,212.86)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"ytick ticks crisp\" d=\"M63,0h-5\" transform=\"translate(0,142.1)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"ytick ticks crisp\" d=\"M63,0h-5\" transform=\"translate(0,71.35)\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; stroke-width: 1px;\"/><g class=\"ytick\"><text text-anchor=\"end\" x=\"55.6\" y=\"4.199999999999999\" transform=\"translate(0,283.61)\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\">50</text></g><g class=\"ytick\"><text text-anchor=\"end\" x=\"55.6\" y=\"4.199999999999999\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(0,212.86)\">100</text></g><g class=\"ytick\"><text text-anchor=\"end\" x=\"55.6\" y=\"4.199999999999999\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(0,142.1)\">150</text></g><g class=\"ytick\"><text text-anchor=\"end\" x=\"55.6\" y=\"4.199999999999999\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(36, 36, 36); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(0,71.35)\">200</text></g></g><g class=\"overaxes-above\"/></g></g><g class=\"polarlayer\"/><g class=\"smithlayer\"/><g class=\"ternarylayer\"/><g class=\"geolayer\"/><g class=\"funnelarealayer\"/><g class=\"pielayer\"/><g class=\"iciclelayer\"/><g class=\"treemaplayer\"/><g class=\"sunburstlayer\"/><g class=\"glimages\"/><defs id=\"topdefs-d475f1\"><g class=\"clips\"/></defs><g class=\"layer-above\"><g class=\"imagelayer\"/><g class=\"shapelayer\"/></g><g class=\"infolayer\"><g class=\"g-gtitle\"><text class=\"gtitle\" x=\"175\" y=\"15\" text-anchor=\"middle\" dy=\"0em\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 17px; fill: rgb(36, 36, 36); opacity: 1; font-weight: normal; white-space: pre;\">Test set predictions with 10% error lines</text></g><g class=\"g-xtitle\"><text class=\"xtitle\" x=\"202\" y=\"339.70625\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(36, 36, 36); opacity: 1; font-weight: normal; white-space: pre;\">Predicted weight (kg)</text></g><g class=\"g-ytitle\" transform=\"translate(4.7841796875,0)\"><text class=\"ytitle\" transform=\"rotate(-90,10.215625000000003,160.5)\" x=\"10.215625000000003\" y=\"160.5\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(36, 36, 36); opacity: 1; font-weight: normal; white-space: pre;\">Actual weight (kg)</text></g></g></svg>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = px.scatter(y=y_test, x=y_pred_test, \n",
    "                 title=\"Test set predictions with 10% error lines\",\n",
    "                 width=350, height=350)\n",
    "fig.update_traces(marker=dict(size=4))\n",
    "\n",
    "fig.add_trace(go.Scatter(x=[60, 200], y=[60, 200], name='0% error',\n",
    "                         mode='lines',\n",
    "                         marker=dict(color='green')))\n",
    "fig.add_trace(go.Scatter(x=[60, 200], y=[66, 220], name='10% error',\n",
    "                         mode='lines',\n",
    "                         marker=dict(color='red')))\n",
    "fig.add_trace(go.Scatter(x=[60, 200], y=[54, 180], name='-10% error',\n",
    "                         mode='lines',\n",
    "                         marker=dict(color='red')))\n",
    "\n",
    "fig.update_layout(showlegend=False)\n",
    "xlabel(fig, \"Predicted weight (kg)\")\n",
    "ylabel(fig, \"Actual weight (kg)\")\n",
    "margin(fig, t=30)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The 10% lines lie farther from the prediction line for larger weights.\n",
    "\n",
    "We've accomplished our goal!\n",
    "We have a model that uses easy-to-get measurements, is simple enough to explain on an instruction sheet, and makes predictions within 10% of the actual donkey weight.\n",
    "Next, we summarize this case study and reflect on our model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
